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    The new era of artificial intelligence
    Nanning ZHENG
    Chinese Journal of Intelligent Science and Technology    2019, 1 (1): 1-3.   DOI: 10.11959/j.issn.2096-6652.201914
    Abstract6733)   HTML1451)    PDF(pc) (506KB)(5897)       Save

    The goal of artificial intelligence (AI) is to make machines learn,think and understand like human beings,with the focus of using computers to imitate human intelligence.It integrates knowledge of multi-disciplines including intuitive reasoning (with all kinds of physical and social common senses),computer vision,natural language perception and interaction,and machine learning.Hybrid-augmented intelligence is the typical feature of the next generation of AI,and cognitive computing of visual and auditory information is the core research content.Therefore,comprehending the human visual and auditory cognition mechanism and building its computable model is of vital significance for AI’s research and development.

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    Artificial intelligence is entering the post deep-learning era
    Bo ZHANG
    Chinese Journal of Intelligent Science and Technology    2019, 1 (1): 4-6.   DOI: 10.11959/j.issn.2096-6652.201913
    Abstract2457)   HTML419)    PDF(pc) (494KB)(5381)       Save

    Points of views on the concept of artificial intelligence (AI),the progress AI has made,and the trend of AI’s future development were presented in this paper.

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    An overview on algorithms and applications of deep reinforcement learning
    Zhaoyang LIU, Chaoxu MU, Changyin SUN
    Chinese Journal of Intelligent Science and Technology    2020, 2 (4): 314-326.   DOI: 10.11959/j.issn.2096-6652.202034
    Abstract1358)   HTML336)    PDF(pc) (2994KB)(1831)       Save

    Deep reinforcement learning (DRL) is mainly applied to solve the perception-decision problem, and has become an important research branch in the field of artificial intelligence.Two kinds of DRL algorithms based on value function and policy gradient were summarized, including deep Q network, policy gradient as well as related developed algorithms.In addition, the applications of DRL in video games, navigation, multi-agent cooperation and recommendation field were intensively reviewed.Finally, a prospect for the future research of DRL was made, and some research suggestions were given.

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    A survey on vehicle re-identification
    Kai LIU, Yidong LI, Weipeng LIN
    Chinese Journal of Intelligent Science and Technology    2020, 2 (1): 10-25.   DOI: 10.11959/j.issn.2096-6652.202002
    Abstract1525)   HTML445)    PDF(pc) (2568KB)(1630)       Save

    Given a vehicle image,vehicle re-identification aims to find the same vehicle caught by other cameras,it can be regarded as a sub-problem of image retrieval.In the real traffic surveillance system,vehicle re-identification can play a role in locating,supervising and criminal investigation of target vehicles.With the rise of deep neural networks and the release of large-scale dataset,improving the accuracy and efficiency of vehicle re-identification has become a research focus in the field of computer vision and multimedia in recent years.The vehicle re-identification methods from different perspectives were classified,and the overview,comparison and analysis in terms of feature extraction,design and performance were given in detail,and the challenges and future trends of vehicle re-identification were predicted.

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    Decentralized autonomous organizations:the state of the art,analysis framework and future trends
    Wenwen DING,Shuai WANG,Juanjuan LI,Yong YUAN,Liwei OUYANG,Fei-Yue WANG
    Chinese Journal of Intelligent Science and Technology    2019, 1 (2): 202-213.   DOI: 10.11959/j.issn.2096-6652.201917
    Abstract2000)   HTML251)    PDF(pc) (1604KB)(1489)       Save

    The decentralized autonomy is not a new concept,the self-organization phenomenon in natural ecosystems,the cyber movement organizations on the Internet,and the distributed artificial intelligence,etc.,can all be regarded as its early manifestations.In recent years,the rapid development of block chain technology has spawned the emergence of the so-called decentralized autonomous organization (DAO),which is a new organization form that the management and operational rules are typically encoded on block chain in the form of smart contracts,and can autonomously operate without centralized control or third-party intervention.Therefore,DAO is expected to become a new and effective organization to deal with uncertain,diverse and complex environments.Defining the conception and features is the first priority.Furthermore,the five layer structural model of DAO analyzing frame to analyze typical Aragon model was proposed and the current issues as well as the research direction in future were discussed,hoping to provide significant guidance and reference for following researchers.

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    Research on architecture and system deployment of intelligent power plant based on digital twin
    Haidong FAN
    Chinese Journal of Intelligent Science and Technology    2019, 1 (3): 241-248.   DOI: 10.11959/j.issn.2096-6652.201930
    Abstract357)   HTML35)    PDF(pc) (4584KB)(1241)       Save

    Under the call of structural reform of energy supply and clean,efficient and intelligent coal-fired power production in China,based on the analysis of the research and practice status of intelligent power plant,combined with digital twin theory and methods,production and operation activities and elements of power plants were virtualized and digitized with the industrial big data platform and management cloud platform as the core,the intelligent power plant architecture were constructed including decision-making,intelligent supervision,intelligent control and intelligent equipment,which covered all aspects of production and operation of power plant equipment,so that the power plant had the characteristics of comprehensive perception,collaborative optimization,prediction and early warning and scientific decision-making.

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    Design of transnational and intercontinental electricity market with blockchain and token economics
    Siyuan CHEN, Yuyang BAI, Jun ZHANG, Fei-yu WANG
    Chinese Journal of Intelligent Science and Technology    2019, 1 (1): 96-105.   DOI: 10.11959/j.issn.2096-6652.201910
    Abstract1522)   HTML72)    PDF(pc) (2573KB)(1087)       Save

    Transnational and intercontinental electricity trading (TIET) is a fundamental enabling component and efficient method to the development of Global Energy Internet (GEI),which aims to build an energy model centered on electricity consumption.The problems faced by TIET was analyzed,and a transnational and intercontinental electricity market (TIEM) based on blockchain and token economics was proposed.The TIEM was divided into five components,and each component was described and modeled respectively.A scale-up power grid based IEEE 39-nodes system was used to analyze the proposed market.The simulation results show that TIEM based on blockchain and token economy can ensure the effective implementation of cross-regional and multi-agent electricity transactions,and also encourage the generation companies (GENCOs) to participate in electricity market with clean energy.

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    A survey of UAV-based edge intelligent computing
    Chao DONG,Yun SHEN,Yuben QU
    Chinese Journal of Intelligent Science and Technology    2020, 2 (3): 227-239.   DOI: 10.11959/j.issn.2096-6652.202025
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    Edge intelligent computing refers to the offloading of computationally intensive tasks generated by user nodes to edge servers with stronger computing capabilities for processing.Unmanned aerial vehicle (UAV)-based edge intelligent computing combines intelligent drone platforms on this basis and utilizes them with the advantages of strong mobility and easy deployment,it can provide edge computing services for ground user equipment more quickly and flexibly.At the same time,drones can also be used as user nodes to off load their computationally intensive tasks to the ground edge server for execution.Aiming at two different scenarios of UAV as a user node or an edge server,the current research on edge intelligent computing based on UAV is classified and summarized according to different optimization goals such as minimizing energy consumption,minimizing delay and maximizing utility,and the next research direction is considered and prospected.

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    Formation control of mobile robots with UWB localization technology
    Yajun ZHENG,Lei XUE,Lu DONG,Qingling WANG
    Chinese Journal of Intelligent Science and Technology    2019, 1 (1): 83-87.   DOI: 10.11959/j.issn.2096-6652.201907
    Abstract1389)   HTML46)    PDF(pc) (1463KB)(865)       Save

    In this paper,a novel multi-mobile robots formation control algorithm based on ultra-wideband (UWB) location technology was proposed.UWB location technology is relatively mature but is less applied to formation control problem.The framework of systems and hardware design of mobile multi-robot systems were first presented.Then,the systems model was established and the corresponding distributed control algorithm was proposed.Finally,the stability of multi-robot systems was proved and one simulation example was given to show the effectiveness of the proposed formation control algorithm.

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    Reinforcement learning:toward action-knowledge merged intelligent mechanisms and algorithms
    Fei-Yue WANG,Dongpu CAO,Qinglai WEI
    Chinese Journal of Intelligent Science and Technology    2020, 2 (2): 101-106.   DOI: 10.11959/j.issn.2096-6652.202011
    Abstract753)   HTML166)    PDF(pc) (1260KB)(817)       Save

    This article discusses briefly the history,the state of the art and the future of reinforcement learning,and outlines a roadmap of evolution from learning by doing,doing with planning to parallel intelligence that combining learning virtually in artificial systems and acting accordingly in actual systems.

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    Dynamical modeling and intelligent control of space soft manipulator
    Xiang ZHANG,Hongwei LIU,Zhuoqun LIU,Zhenguo YAN,Xiaoqian CHEN,Yiyong HUANG
    Chinese Journal of Intelligent Science and Technology    2019, 1 (1): 52-61.   DOI: 10.11959/j.issn.2096-6652.201905
    Abstract952)   HTML32)    PDF(pc) (5770KB)(786)       Save

    Space intelligent soft manipulator shows a broad prospect in the application of on-orbit service,due to its lightweight,dexterity and foldability.In this paper,a design of a modular soft manipulator with omnidirectional drivers was proposed.The dynamical model of the proposed soft manipulator was developed based on the rigid-flexible coupling system dynamics.The detection and recognition algorithm for space non-cooperative objects was designed based on deep regression convolution neural network.Both the dynamical model and the algorithm are the foundation for the intelligent control of the soft manipulator.Moreover,an experiment system of the soft manipulator was designed and developed,and the autonomous motion control and the recognition algorithm were validated.

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    Parallel agriculture:intelligent technology toward smart agriculture
    Mengzhen KANG,Xiujuan WANG,Jing HUA,Haoyu WANG,Fei-Yue WANG
    Chinese Journal of Intelligent Science and Technology    2019, 1 (2): 107-117.   DOI: 10.11959/j.issn.2096-6652.201904
    Abstract905)   HTML50)    PDF(pc) (1674KB)(755)       Save

    Agricultural production is featured by strong uncertainty,diversity and complexity.Production benefit is related to natural conditions,national policies and market environment.Internet brings new challenges and chances to the management in agriculture.Generally speaking,smart agriculture refers to smart control on full production chain including management and service,using ICT techniques,in order to achieve high quality,high efficiency,security and controllability.Based on a brief introduction on the techniques related to these three aspects,the parallel agriculture as the methodology for decision support in smart agriculture was proposed,with artificial system for description intelligence,computational experiments for prediction intelligence,and parallel execution for prescription intelligence.Moreover,the link to agricultural enterprise resource planning (ERP) system,manufacturing execution system (MES) and process control system (PCS) was discussed.As China was developing large-scale agricultural production,methodology for managing scaled agriculture production was provided.

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    NFT: blockchain-based non-fungible token and applications
    Rui QIN, Juanjuan LI, Xiao WANG, Jing ZHU, Yong YUAN, Fei-Yue WANG
    Chinese Journal of Intelligent Science and Technology    2021, 3 (2): 234-242.   DOI: 10.11959/j.issn.2096-6652.202125
    Abstract1201)   HTML122)    PDF(pc) (871KB)(723)       Save

    Non-fungible token (NFT) based on blockchain is a kind of digital asset ownership recorded on blockchain, which is unique, irreplaceable and indivisible.It has been widely used in collectibles, encrypted artworks and games.Firstly, the concepts, characteristics and development processes of NFT were mainly introduced, and its core elements and typical application fields were analyzes.The problems and risks faced by NFT in the aspects of property right, value, technology and supervision were also pointed out.After that, the related literatures on NFT were reviewed, and the research issues of NFT in value evaluation, transaction mode and pricing were proposed.Finally, the trend of NFT driven digital capitalization was prospected.

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    Parallel transportation:virtual-real interaction for intelligent traffic management and control
    Yisheng LV,Yuanyuan CHEN,Junchen JIN,Zhenjiang LI,Peijun YE,Fenghua ZHU
    Chinese Journal of Intelligent Science and Technology    2019, 1 (1): 21-33.   DOI: 10.11959/j.issn.2096-6652.201908
    Abstract1502)   HTML97)    PDF(pc) (6986KB)(713)       Save

    The concept,architecture,methods and applications of parallel transportation systems were introduced.The main idea is to build software defined artificial transportation systems for specific traffic application tasks and scenarios;use computational experimental methods for experiments,analysis,evaluation,prediction,learning,and optimization;and parallel execution is conducted for management and control of urban transportation systems,leading to virtual-real interactive parallel intelligence.Parallel traffic management and control is an extension and application of ACP approach,which emphasizes using virtual-real interactive ways to generate parallel intelligence for urban transportation systems,towards improving the intelligence of urban traffic management and control.

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    Parallel nuclear power:intelligent technology for smart nuclear power
    Jiachen HOU,Xisong DONG,Gang XIONG,Jun ZHANG,Ke TAN
    Chinese Journal of Intelligent Science and Technology    2019, 1 (2): 192-201.   DOI: 10.11959/j.issn.2096-6652.201912
    Abstract1174)   HTML27)    PDF(pc) (3801KB)(711)       Save

    A framework to incorporate nuclear plants using the ACP based parallel system theory was proposed.This research framework has established a convenient and safe platform for nuclear power plants to experiment,learn and work in complex environments,namely parallel nuclear power system.Proceeding from the basic concept of parallel nuclear power,the basic framework of parallel nuclear power system was proposed,and the elementary functions and implementation methods of description,prediction and guidance module were also introduced.The key technologies were also further discussed.At last,this paper looks forward to the nuclear power system application in emergency,and the future development direction of parallel nuclear power system was proposed.

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    Development prospect of fuzzy system oriented to interpretable artificial intelligence and big data
    Dewang CHEN,Jijie CAI,Yunhu HUANG
    Chinese Journal of Intelligent Science and Technology    2019, 1 (4): 327-334.   DOI: 10.11959/j.issn.2096-6652.201937
    Abstract445)   HTML59)    PDF(pc) (907KB)(710)       Save

    As a universal approximator with strong interpretability,fuzzy system has been widely used in various fields.Although the current theoretical research on fuzzy system is not mature enough,there are still many problems such as too many rules,optimization difficulties,dimension curse,which make it difficult to deal with high-dimensional large data.Although deep neural network has made remarkable progress and can process large data such as image and voice very well,its interpretability is not good and it is difficult to be used in important security-related occasions.Therefore,it is necessary to study an interpretable artificial intelligence algorithm based on fuzzy system.Combining the advantages of deep neural network and fuzzy system,it is possible to solve the problem of high dimensional and large data by studying the deep fuzzy system and its algorithm.The development history and research progress of fuzzy system separately was mainly reviews,and its future development direction according to its existing problems was pointed out,and the summary of this article and the prospect for further research about the problems were given.

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    Three-dimensional reconstruction cloud studio based on semi-supervised generative adversarial networks
    Chong YU
    Chinese Journal of Intelligent Science and Technology    2019, 1 (1): 70-82.   DOI: 10.11959/j.issn.2096-6652.201909
    Abstract1325)   HTML39)    PDF(pc) (12802KB)(703)       Save

    Because of the intrinsic complexity in computation,three-dimensional (3D) reconstruction is an essential and challenging topic in computer vision research and applications.The existing methods for 3D reconstruction often produce holes,distortions and obscure parts in the reconstructed 3D models.While the 3D reconstruction algorithms based on machine learning can only reconstruct voxelized 3D models for simple isolated objects,they are not adequate for real usage.From 2014,the generative adversarial network (GAN) is widely used in generating unreal dataset and semi-supervised learning.So the focus of this paper is to achieve high quality 3D reconstruction performance by adopting GAN principle.A novel semi-supervised 3D reconstruction framework,namely SS-GAN-3D was proposed,which can iteratively improve any raw 3D reconstruction models by training the GAN models to converge.This new model only takes 2D observation images as the weak supervision,and doesn’t rely on prior knowledge of shape models or any referenced observations.Finally,through qualitative and quantitative experiments and analysis,this new method shows compelling advantages over the current state-of-the-art methods on Tanks & Temples and ETH3D reconstruction benchmark datasets.Based on SS-GAN-3D,the 3D reconstruction studio solution was proposed.

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    Research review and prospect of intelligent dynamic wireless charging system for electric vehicles
    Hongye SU, Ze ZHOU, Zhitao LIU, Liyan Zhang
    Chinese Journal of Intelligent Science and Technology    2020, 2 (1): 1-9.   DOI: 10.11959/j.issn.2096-6652.202001
    Abstract409)   HTML92)    PDF(pc) (4720KB)(646)       Save

    In order to solve the problems of large volume of battery and mileage anxiety,and accelerate application of electric vehicles,dynamic wireless charging system (DWCS) was presented and studied.In this paper,the basic framework of intelligent DWCS for electric vehicles was introduced,and a detailed review of the research results for DWCS by the researchers in the world was described,including the circuit structure and system modeling,electric vehicle positioning,control strategy of DWCS and the interaction with smart grid,etc.Then the intelligent DWCS of electric vehicle was prospected,mainly including system structure and optimization,the integration with the driverless technology,the integration of technologies and the collaborative optimization strategy with power grid and traffic network.The research direction and development trend in the future were also analyzed in this paper.

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    Technical analysis of typical intelligent game system and development prospect of intelligent command and control system
    Xiangang LI,Qiang LI
    Chinese Journal of Intelligent Science and Technology    2020, 2 (1): 36-42.   DOI: 10.11959/j.issn.2096-6652.202004
    Abstract371)   HTML44)    PDF(pc) (549KB)(599)       Save

    In the future era of intelligence,the massive and heterogeneous battlefield data and the widespread use of unmanned platforms will accelerate the expansion of the combat space from the physical and information domains to the cognitive domains,which will put forward higher requirements for the accuracy,timeliness and effectiveness of command and control,and the intelligence of command and control will become the general trend.Based on the analysis of typical foreign intelligent command and control system,the machine game technology development course was clarified,the challenge of applying machine game technology to intelligent command and control system was analyzed,the future intelligent command and control in combat training,operational innovation and prospective of system architecture and implementation was put forward,so as to provide reference and enlightenment for the future development of command and control system.

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    The application of deep learning in data-driven modeling of process industries
    Xiaofeng YUAN,Yalin WANG,Chunhua YANG,Weihua GUI
    Chinese Journal of Intelligent Science and Technology    2020, 2 (2): 107-115.   DOI: 10.11959/j.issn.2096-6652.202012
    Abstract452)   HTML61)    PDF(pc) (1147KB)(581)       Save

    Deep learning is an artificial intelligence technique developed in recent years.Compared with traditional shallow models,deep learning has a strong ability of feature representation and function fitting.It can extract hierarchical features from massive data,which has great potential for data-driven modeling in process industries.Firstly,the history of deep learning was introduced.Then,four widely used deep networks and their applications were introduced in data-driven modeling of process industries.At last,the conclusions about deep learning and its applications in process in dustries were given.

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    Method of functional brain network modeling with group similarity constraint for mild cognitive impairment classification
    Weikai LI,Xin GAO,Tongjian JI,Zhengxia WANG
    Chinese Journal of Intelligent Science and Technology    2019, 1 (2): 145-153.   DOI: 10.11959/j.issn.2096-6652.201922
    Abstract432)   HTML23)    PDF(pc) (1712KB)(570)       Save

    Functional brain network provides an effective biomarker for understanding brain activation patterns,the development of neurodegenerative diseases,and the structure of brain signaling.How to use priori information to build accurate brain network is particularly important in subsequent applications.A functional brain network construction model based on group similarity constraints was proposed.By introducing a tensor low rank constraint and using the nuclear norm of the tensor,a brain network group with a low rank prior in the group was solved.The group similarity constraints to shrink the solution space of the brain network was used,thus constructing a better functional brain network effectively.For evaluating the performance of the proposed method,the constructed brain network was adopted for the discriminative task of mild cognitive impairment.The experimental results show that the proposed functional brain network modeling method based on group similarity constraints can construct more discriminative brain network.In addition,based on the brain network constructed by the proposed method,the significant connections consistent with previous studies are obtained,and the effectiveness of the proposed method is further verified.

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    Algorithm design for food-picking combining deep learning and biometrics recognition
    Niya CHEN,Jiayang RUAN,Jinmiao HUANG,Wei YANG
    Chinese Journal of Intelligent Science and Technology    2019, 1 (1): 88-95.   DOI: 10.11959/j.issn.2096-6652.201906
    Abstract1079)   HTML32)    PDF(pc) (6028KB)(548)       Save

    Irregular-shape food picking and processing is a common problem in industrial automation,which can be difficult for classical image processing techniques,because of the big variations in food shape and characteristics,also the high-performance requirements in both algorithm accuracy and speed.In this paper,a hybrid method based on deep learning and feature recognition was proposed,which first roughly localized the target point based on deep learning model,and then created a search range accordingly.After that,based on biological feature analysis,target point could be accurately localized in the search range.Based on the data of shrimps,a kind of common food,the performance of the proposed method was tested.The shrimp images were pre-processed and used to train the deep learning model for rough localization.Then the shrimp body pose was normalized for edge extraction after proper rotation and projection.The extracted edge curve in search range was analyzed to accurately localize the target joint point.The validation results based on a test set including 1000 samples prove the feasibility of the method – the final detection rate of the proposed hybrid method is 97%.The performance meets industrial requirements on this case.

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    AI in game intelligence—from multi-role game to parallel game
    Yu SHEN,Jinpeng HAN,Lingxi LI,Fei-Yue WANG
    Chinese Journal of Intelligent Science and Technology    2020, 2 (3): 205-213.   DOI: 10.11959/j.issn.2096-6652.202023
    Abstract305)   HTML51)    PDF(pc) (6641KB)(539)       Save

    The domestic and overseas research progress of artificial intelligence technology in the field of games was summarized and the significance of the research progress in the field of games for real life was analyzed.In view of the gap between simulation and reality in model based methods and the lack of generality of the model-based approach in reinforcement learning,the idea and method of parallel game were put forward,and the advance of parallel game in solving the existing problems of single-role game and multi-role game was introduced.The parallel game method will be the cornerstone of the general artificial intelligence.

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    Research on digital quadruplets in cyber-physical-social space-based parallel driving
    Teng LIU, Xiao WANG, Yang XING, Yu GAO, Bin TIAN, Long CHEN
    Chinese Journal of Intelligent Science and Technology    2019, 1 (1): 40-51.   DOI: 10.11959/j.issn.2096-6652.201902
    Abstract1786)   HTML59)    PDF(pc) (26943KB)(519)       Save

    Parallel driving is an advanced,cloudy and unified approach for connected automated driving that includes operation management,online condition monitoring and emergency take-over.The digital quadruplets in parallel driving,which include physical vehicle,descriptive vehicle,predictive vehicle and prescriptive vehicle were defined.First,the content and framework of the parallel driving and digital quadruplets were introduced.Then,the details of the descriptive,predictive and prescriptive vehicles were given.Finally,the applications of the digital quadruplets in mining and logistics scenarios were discussed.

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    A novel blockchain-based surveillance and early-warning technology for infectious diseases
    Liwei OUYANG,Yong YUAN,Xinhu ZHENG,Jun ZHANG,Fei-Yue WANG
    Chinese Journal of Intelligent Science and Technology    2020, 2 (2): 135-143.   DOI: 10.11959/j.issn.2096-6652.202015
    Abstract384)   HTML51)    PDF(pc) (1285KB)(510)       Save

    The key of early prevention and control of infectious diseases is to use the early warning technology and system to monitor the abnormal occurrence and trend of infectious diseases.There are still some problems in the existing infectious diseases automated-alert and response systems,such as lack of intelligence,poor efficiency in exchange of key information,as well as difficulties in distributed decision-making.Based on the distributed blockchain architecture,a novel blockchain-based surveillance and early-warning technology for infectious diseases was proposed,leveraging emerging information technologies including artificial intelligence,big data and smart contract.The technology could aggregate monitoring forces from multiple parties efficiently,integrate various early warning technologies flexibly,and establish a distributed and collaborative monitoring environment for knowledge integration and intelligent interconnection with guaranteed security and privacy protection.In this framework,smart contract was served as a “software-defined agent” to fuse decisions,monitor the outbreak,and issue warnings in an automatic and real-time fashion,so as to meet the key requirements of accuracy and timeliness,and avoid the decision bias of single evidence.

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    Research and application on combustion optimization of coal-fired boiler in thermal power plant based on artificial intelligence technology
    Peifeng NIU,Yunpeng MA,Xinxin ZHANG,Xiaobin HU
    Chinese Journal of Intelligent Science and Technology    2019, 1 (2): 163-170.   DOI: 10.11959/j.issn.2096-6652.201925
    Abstract891)   HTML25)    PDF(pc) (1286KB)(491)       Save

    In order to reduce the NOxemission concentration and coal consumption of coal-fired boilers in thermal power plants,the sample increment quantum neural network and an improved quantum bee colony algorithm were proposed.The quantum sample incremental feed-forward neural network can dynamically establish a comprehensive model of Nitrogen and Oxygen emission concentration and boiler coal consumption of coal-fired boiler,and can realize rolling optimization of the model.Based on the established comprehensive model,the optimization of the primary and secondary air volume and coal and the opening degree of each secondary air valve were realized by using the improved quantum bee colony algorithm.Based on the above two methods,a set of intelligent combustion optimization software for coal-fired boiler was developed and applied to the 330 MW boiler of a thermal power plant.The test results show that the Nitrogen and Oxygen emission concentration and the coal consumption of the boiler have been reduced in varying degrees.It is shown that the modeling method and the optimization algorithm are effective.

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    General game AI with statistical forward planning algorithms
    LUCAS Simon, Tianyu SHEN, Xiao WANG, Jie ZHANG
    Chinese Journal of Intelligent Science and Technology    2019, 1 (3): 219-227.   DOI: 10.11959/j.issn.2096-6652.201935
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    Statistical forward planning (SFP) algorithms use a simulation model (also called forward model) to adaptively search for effective sequences of actions.They offer a simple and general way to provide rapidly adaptive AI controllers for a variety of games.The two powerful SFP example algorithms:Monte Carlo tree search and rolling horizon evolution were introduced in this paper and key insights into their working principles were provided.It is demonstrated that the algorithms are able to play a variety of video games surprisingly well without the need for any prior training.

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    A survey of affective brain-computer interface
    Bao-Liang LU, Yaqian ZHANG, Wei-Long ZHENG
    Chinese Journal of Intelligent Science and Technology    2021, 3 (1): 36-48.   DOI: 10.11959/j.issn.2096-6652.202104
    Abstract535)   HTML108)    PDF(pc) (921KB)(479)       Save

    An important research goal in emotion artificial intelligence is to make machines understand and recognize human emotions in real-time and facilitate human-computer interaction in a more natural and friendly way.Affective brain-computer interface (aBCI) is a type of BCI that can recognize and/or modulate human emotion.Thus, aBCI plays a critical role in promoting emotion artificial intelligence.The basic concepts and recent research development of aBCI were summarized, and the applications of aBCI in a wide range of domains were outlined.The roles that the aBCI can play in the development of artificial general intelligence and the challenges faced by the aBCI research community were discussed.

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    Social energy:mining energy from the society
    Jun ZHANG,Fei-yue WANG,Zhou FANG
    Chinese Journal of Intelligent Science and Technology    2019, 1 (1): 7-20.   DOI: 10.11959/j.issn.2096-6652.201901
    Abstract1742)   HTML39)    PDF(pc) (19145KB)(473)       Save

    The inherent nature of energy,i.e.,physicality,sociality and informatization,implies the inevitable and intensive interaction between energy systems and social systems.In this paper,the nature of energy was proposed,and then the concept and intention of social energy systems for electrical power were proposed.A general methodology of establishing and investigating social energy was proposed.A case study on the University of Denver (DU) campus grid was provided and studied to demonstrate the social energy concept.In the concluding remarks,the technical pathway was discussed in both social and nature sciences,to social energy,and our vision on its future.

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    Cloud native robot system based on edge computing
    Dawei WANG,Zhuo WANG,Peng WANG,Zhigang WANG,Haitao WANG
    Chinese Journal of Intelligent Science and Technology    2020, 2 (3): 275-283.   DOI: 10.11959/j.issn.2096-6652.202030
    Abstract385)   HTML41)    PDF(pc) (2651KB)(471)       Save

    With the rapid development of artificial intelligence,the global robot market continues to grow quickly,and the capabilities of robots have evolved from performing fixed operations to the ability to autonomously sense,understand and make decisions.However,to achieve large-scale application of robots,robots need to have powerful computing capabilities and low deployment costs under the constraints of limited power consumption.Using edge computing to provide more cost-effective services,enhance the computing power of the robot body,and achieve large-scale deployment is the key to achieving this goal.The challenges faced by robot systems with the edge enhancement were analyzed,the concept of cloud-native robot systems based on edge computing was proposed,and four feasible technical solutions for implementing the system were discusses.The cloud-native robot system is the inevitable direction for the development of robot systems from intelligent systems based on robot ontology to cloud-edge-end fusion multi-robot collaborative intelligent systems and the key technology for promoting the large-scale application of robots.

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    Federated visualization:a new model for privacy-preserving visualization
    Yating WEI,Zhiyong WANG,Shuyue ZHOU,Wei CHEN
    Chinese Journal of Intelligent Science and Technology    2019, 1 (4): 415-420.   DOI: 10.11959/j.issn.2096-6652.201946
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    The concept,architecture,methods and applications of federated visualization were introduced.The federated visualization framework is capable of encrypting and training a visual model that reflect the characteristics of the entire data for specific tasks and scenarios.The federated visualization framework is an extension and application of federated learning,which emphasized using mutual benefit and win-win federal cooperation to visually analyze multi-source data under the premise of ensuring data privacy,towards breaking down data barriers in various fields and industries and realizing the sharing of data and knowledge.

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    Parallel control and digital twins:control theory revisited and reshaped
    Fei-Yue WANG
    Chinese Journal of Intelligent Science and Technology    2020, 2 (3): 293-300.   DOI: 10.11959/j.issn.2096-6652.202032
    Abstract457)   HTML62)    PDF(pc) (1524KB)(458)       Save

    After a brief discussion of the origin and development of classic control,intelligent control,and parallel control,the mathematical equations for a class of parallel control systems was presented for problems with high precision digital twin models.The key idea was modeling the time derivative of system control instead of system control itself,which leads to differential equation based control rather than algebraic relationship based control,made the system and its control symmetrical in both form and content mathematically,thus provided the foundation for implementing human-like control and intelligent control.Same idea was also applied to system output equations,and proposed a new way for active sensing and design of parallel sensors.Preliminary results along those lines are illustrated and discussed.

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    Research on path curvature smoothing method based on energy function for intelligent vehicles
    Qiang SHI,Ming YANG
    Chinese Journal of Intelligent Science and Technology    2020, 2 (2): 161-168.   DOI: 10.11959/j.issn.2096-6652.202018
    Abstract241)   HTML25)    PDF(pc) (5085KB)(454)       Save

    Intelligent vehicles are of great significance in social efficacy such as prevention of traffic accidents,ease traffic congestion and reducing emissions.Path tracking is an important part of intelligent vehicles function,whose controlled object is a complex vehicle-road coupling system.Path curvature smoothness affects path tracking performance.A curvature smoothing method based on energy function was proposed to optimize the smoothness of path curvature.Firstly,an energy function was constructed to characterize the path curvature smoothness.Secondly,aniteration rule was designed to reduce the energy function based on discrete path description.Finally,the constraint of road boundary was considered when the road boundary was known.The experimental results of the real vehicle platform show that the energy function smoothing method can further improve the ride comfort and control accuracy of path tracking on the premise of ensuring the path feasible.The quality of intelligent vehicles is improved.

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    Parallel loading and unloading:smart technology toward intelligent logistics
    Dayong SHEN,Xiao WANG,Sheng LIU
    Chinese Journal of Intelligent Science and Technology    2019, 1 (1): 34-39.   DOI: 10.11959/j.issn.2096-6652.201911
    Abstract1061)   HTML58)    PDF(pc) (2472KB)(452)       Save

    The ACP theory plays an important role in modeling and controlling complex,uncertain systems.Parallel loading and unloading is the integration of this theory in intelligent logistics.The basic framework of the parallel loading and unloading system was proposed in this paper.In this framework,the artificial system was built and updated continuously to describe real loading and unloading process,then computing experiments perform all kinds experiments for predicting all possible development and evaluate the best scheme.Finally,a bridge between the real system and the artificial system was built by the parallel execution and a long-term guidance for the real system could be realized,while artificial system was updated based on information from the real system.

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    An overview of optimal consensus for data driven multi-agent system based on reinforcement learning
    Jinna LI, Weiran CHENG
    Chinese Journal of Intelligent Science and Technology    2020, 2 (4): 327-340.   DOI: 10.11959/j.issn.2096-6652.202035
    Abstract329)   HTML47)    PDF(pc) (815KB)(447)       Save

    Multi-agent system has attracted extensive attention in the past two decades because of its potential applications in engineering, social science and natural science, etc.To achieving the consensus of multi-agent system, it is usually necessary to solve the correlation matrix equation to design the control protocol offline, which requires system model to be known accurately.However, the actual multi-agent system has the characteristics of large-scale, nonlinear coupling, and dynamic change of environment, which makes it very difficult to accurately model the system.This brings challenges to the design of model dependent multi-agent consensus protocol.Reinforcement learning is widely used to solve the optimal control and decision-making problems of complex systems because it can learn the optimal solution of control problems in real time by using the measurement data along the trajectory of the system.The existing theories and methods of online solving the optimal consensus of multi-agent system inreal-time by using reinforcement learning technology were summarized.The application of data-driven reinforcement learning technology in multi-agent system optimal consensus was introduced from the aspects of continuous and discrete, homogenous and heterogeneous, anti-interference robustness and so on.Finally, the future research direction of the optimal consensus problem of multi-agent system based on data-driven technology was discussed.

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    Parallel machine:a framework for the control and management for intelligent machines
    Tianxiang BAI,Zhen SHEN,Yating LIU,Xisong DONG
    Chinese Journal of Intelligent Science and Technology    2019, 1 (2): 181-191.   DOI: 10.11959/j.issn.2096-6652.201915
    Abstract404)   HTML13)    PDF(pc) (2026KB)(429)       Save

    The concept of parallel machine framework as a solution to the challenges of the complexity of intelligent machines was proposed in this paper.The ACP theory was incorporated into intelligent machine field,and a virtual-real interactive pattern was formed in the control and management of machine.The parallel machine concept is composed of the real machine and corresponding software-defined virtual ones,and through which the functionality including describing,predicting and prescription can be achieved.Finally,relevant technologies and potential applications of parallel machine were discussed.

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    Integral back-stepping algorithm for designing the quadrotor aircraft controller
    Yan GUO,Meiping WU,Kanghua TANG,Xueying WANG
    Chinese Journal of Intelligent Science and Technology    2019, 1 (2): 133-139.   DOI: 10.11959/j.issn.2096-6652.201924
    Abstract628)   HTML30)    PDF(pc) (1571KB)(401)       Save

    In view of the problem that the back-stepping algorithm control model is complex and physically difficult to realize,a method of integral back-stepping algorithm for the under-actuated quadrotor aircraft was proposed in this paper.The back-stepping technique based on the Lyapunov stability theory was used to realize the effective tracking control of position and attitude,and ensure the stability of the quadrotor aircraft controller.In order to simplify the controller model,it is proposed to add the integral term in the process of the back-stepping attitude controller design according to the characteristics of the aircraft model,and set the appropriate integral term constant to reduce the burden of the controller and to enhance the practicability of the control algorithm.The controller can realize the stabilization of each attitude,the fixed point,the trajectory track of the position and yaw without error.

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    A review of prediction methods for moving target trajectories
    Wen LIU, Kunlin HU, Yan LI, Zhao LIU
    Chinese Journal of Intelligent Science and Technology    2021, 3 (2): 149-160.   DOI: 10.11959/j.issn.2096-6652.202115
    Abstract267)   HTML45)    PDF(pc) (2312KB)(392)       Save

    With the rapid emergence of mobile terminal equipment in intelligent transportation system, the deep understanding and accurate prediction of moving target trajectories are capable of reducing the traffic accident probability, and promoting the location service-based intelligent transportation applications.The trajectory prediction methods prediction methods for moving target trajectories were reviewed from the data-driven prediction methods and the behavior-driven trajectories prediction methods.Firstly, the data-driven prediction methods were reviewed, including probabilistic statistics, neural networks, deep learning, and hybrid modeling.Then, the basic conceptions of target behavior-driven trajectories prediction methods were analyzed.The corresponding dynamical modeling and intention recognition methods were reviewed.The trajectory prediction applications were briefly analyzed and reviewed, such as target trajectory reconstruction, target abnormal behavior identification, and navigation route planning.Finally, the main problems and development directions related to prediction of moving target trajectories were discussed.

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    Emotion recognition based on brain and machine collaborative intelligence
    Dongjun LIU, Yuhan WANG, Wenfen LING, Yong PENG, Wanzeng KONG
    Chinese Journal of Intelligent Science and Technology    2021, 3 (1): 65-75.   DOI: 10.11959/j.issn.2096-6652.202107
    Abstract269)   HTML40)    PDF(pc) (2762KB)(391)       Save

    Emotion recognition is a direct and effective mode of emotion recognition.Machine learning relies on the formal representation of image expressions, lacks the cognitive representation ability of the brain, and has poor recognition performance on small sample data sets or complex expression (camouflage) data sets.To this end, the formal representation of machine artificial intelligence was combined with the emotional cognitive ability of human brain general intelligence, and a brain-machine collaborative intelligence emotion recognition method was proposed.Firstly, electroencephalogram (EEG) emotional features were extracted from EEG to obtain the brain’s cognitive representation of emotions.Secondly, the visual features of the image were extracted from the emotional image to obtain the machine’s formal representation of the emotion.In order to enhance the generalization ability of the machine model, the transfer adaptation between samples was introduced in the feature learning.After obtaining image visual features and EEG emotional features, the random forest regression model was trained to obtain the brain-machine mapping relationship between image visual features and EEG emotional features.The visual features of the test image were generated through the brain-machine mapping relationship to generate virtual EEG emotional features, and then the virtual EEG emotional features and image visual features were fused for emotion recognition.This method has been verified on the Chinese facial affective picture system (CFAPS) and found that the average recognition accuracy of the seven emotions is 88.51%, which is 3%~5% higher than the image-based method.

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    Overview of intelligent game:enlightenment of game AI to combat deduction
    Yuxiang SUN, Yihui PENG, Bin LI, Jiawei ZHOU, Xinlei ZHANG, Xianzhong ZHOU
    Chinese Journal of Intelligent Science and Technology    2022, 4 (2): 157-173.   DOI: 10.11959/j.issn.2096-6652.202209
    Abstract454)   HTML21)    PDF(pc) (869KB)(389)       Save

    The field of intelligent game has gradually become one of the hotspots of AI research.A series of research breakthroughs have been made in the field of game AI and intelligent wargame in recent years.However, how to develop game AI and apply it to the actual intelligent combat deduction is still facing great difficulties.The overall progress of research in the field of intelligent games in domestic and overseas were explored, the main attribute requirements of intelligent combat deduction was tracked, and it was summarized with the latest advancements in reinforcement learning.The feasibility of developing game AI into intelligent combat deduction were comprehensively analyzed from three dimensions: mainstream research technology in the field of intelligent game, relevant intelligent decision technology and technical difficulties of combat deduction, and finally, some suggestions for the development of future intelligent combat deductiongives were given.This paper can introduce a clear development status and provide valuable research ideas for researchers in the field of intelligent game.

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    Application and practice of machine learning model in real-time anti-fraud in the era of digital finance
    Hanping CAO,Xiaojing ZHANG,Ruijie ZHU,Xiaola HUANG
    Chinese Journal of Intelligent Science and Technology    2019, 1 (4): 342-351.   DOI: 10.11959/j.issn.2096-6652.201939
    Abstract424)   HTML44)    PDF(pc) (3227KB)(386)       Save

    In recent years,with the rapid development of FinTech,digital finance has flourished and brought huge positive effect on society.Meanwhile,new risks have been introduced into banks.For example,the black production related to network security has experienced explosive growth,and telecommunication network fraud has caused property losses to the public.In the era of digital finance,the commercial banks have not only ushered in new opportunities and dynamics,but also faced new challenges and requirements for digital transformation.As a result,e-finance has become a new battlefield.With this context,a real-time anti-fraud machine learning model based on high-dimensional transaction behavior portrait through enhanced RFM feature-derivation and machine learning modeling was established in this paper.Relying on the new technologies such as big data,stream computing,a model application solution to real-time risk control was formed including systematic deployment,model application strategies and iterative model optimization.Through practical observation,the AUC of the model reaches 0.972,which provides a keen insight into fraud risk,realizes millisecond-level risk identification,and promotes risk control ability of e-finance significantly.

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    Research on control algorithm of a four axis air vehicle-inverted pendulum system
    Fanguo KONG,Zhaoxing LI,Jiancun ZHANG,Gang XIONG,R.Nyberg Timo
    Chinese Journal of Intelligent Science and Technology    2019, 1 (2): 140-144.   DOI: 10.11959/j.issn.2096-6652.201916
    Abstract704)   HTML14)    PDF(pc) (928KB)(364)       Save

    Controlling the balance of a movable rod or a wine cup filled with water on a four axis air vehicle is a hard job.A system called four axis air vehicle-inverted pendulum balance control system is needed.With this special kind of balance control system and the idea of a simplified model to replace the complex system for analysis,the performance of a linear four axis vehicle-inverted pendulum on X-Z plane was studied,its dynamic and physical formula was also discussed.The simplified model equipped with the control algorithm of sliding mode control was designed and simulated on the computer with the help of MATLAB.The result shows that the control algorithm works well on the four axis air vehicle-inverted pendulum balance control system and the system has a good performance.

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    Research and application of cloud service system for cold chain
    Shichao CHEN,Bin TIAN,Yisheng LV,Bin HU,Shuangshuang HAN
    Chinese Journal of Intelligent Science and Technology    2019, 1 (2): 125-132.   DOI: 10.11959/j.issn.2096-6652.201919
    Abstract457)   HTML12)    PDF(pc) (4838KB)(348)       Save

    For the current challenges of lacking cold chain logistics information,traceability and other issues,the end-to-end cold chain cloud service system was designed in this paper,based on Internet of Things (IoT) technology and micro-service system architecture.Full cycle for cold chain logistics and data monitoring in different business scenarios could be realized by this system.It can solve the problem of information isolated island and data sharing in the existing cold chain monitoring system,and meet the actual demand of the constant chain of pharmaceutical cold chain monitoring.The designed cold chain cloud service system includes intelligent monitoring terminal,cloud service management platform and cold chain manager App.This system can be applied to logistics of medicine,fresh,fruit,flowers,etc.In this paper,the application of the system in the pharmaceutical industry was described in detail,especially in the three business scenarios of storage,transportation and sales of pharmaceutical cold chain.The proposed system is stable and has been applied in commercial operation.Besides,its advantages have been approved by many users in the pharmaceutical industry.

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    Parallel security:generative adversarial systems for intelligent security in CPSS
    Yidong LI,Jun ZHANG,Yaodong TAO,Wei WANG,Yuanxiang GU,Fei-Yue WANG
    Chinese Journal of Intelligent Science and Technology    2020, 2 (2): 194-202.   DOI: 10.11959/j.issn.2096-6652.202022
    Abstract219)   HTML37)    PDF(pc) (2439KB)(346)       Save

    Developing technologies such as AI and big data are changing the landscape of cybercrime for both attackers and defenders.Traditional defense technology mainly use the passive detect-then-defend model,which is hard to meet the security protection requirements brought by new attack characteristics.A novel security framework,named parallel security was proposed,which aimed at providing a comprehensive solution with descriptive security,predictive security and prescriptive security.The main idea was based on the ACP theory of parallel intelligent,and integrated new methods such as generative adversarial leaning model,parallel blockchain.Human elements,sociology and psychology were taken as an important component in the framework,in order to enhance the immunity of the system.In addition,a parallel security based platform was design and developed for several typical scenarios in the field of industrial internet as a proof of concept.

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    Parallel light field: the framework and processes
    Fei-Yue WANG, Xiangbing MENG, Sicong DU, Zheng GENG
    Chinese Journal of Intelligent Science and Technology    2021, 3 (1): 110-122.   DOI: 10.11959/j.issn.2096-6652.202112
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    The light field is the collection of lights in the environment, and the acquisition, calculation and display of light field information are extremely challenging and complex issues.The ACP-based theory of parallel light field provides a new and effective way to solve this problem.It used the acquired light field information from the actual physical world to construct an enhanced light field of artificial world.And guided by the light field and other information from the actual physical world, light field experiments were conducted in the enhanced light field in all artificial world to obtain the optimal light field acquisition or display schemes.Finally, the parallel optimization of the physical and artificial light fields was established through the process of parallel execution, so that the entire system become a closed-loop system.In this way, intelligent light field acquisition and display were achieved, and a real-virtual theoretical framework for light field information processing and utilization was established.

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    Parallel art:artistic creation under human-machine collaboration
    Chao GUO,Yue LU,Yilun LIN,Fan ZHUO,Fei-Yue WANG
    Chinese Journal of Intelligent Science and Technology    2019, 1 (4): 335-341.   DOI: 10.11959/j.issn.2096-6652.201938
    Abstract240)   HTML34)    PDF(pc) (838KB)(332)       Save

    The artistic creation of machine has drawn considerable attention and achieved significant development in recent years.There are more and more artworks processed partially by specific algorithms,or even created entirely by machines.Despite their popularity,it is hard for these artworks to be accepted by humans because of their underwhelming sensory impacts and lack of empathy.However,their impact is highly concerned by the art community.A theoretical framework called the parallel art system was proposed to solve the technical and human-machine-relationship challenges in artistic creation.The system aims to build a partnership between humans and machines,enabling them to collaborate in a parallel manner,and even provide a new way to integrate human emotion and machine logic.

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    A dynamic object tracking system of industrial robots based on visual servoing technology
    Yichao MAO,Qi LU
    Chinese Journal of Intelligent Science and Technology    2019, 1 (1): 62-69.   DOI: 10.11959/j.issn.2096-6652.201903
    Abstract868)   HTML20)    PDF(pc) (7025KB)(330)       Save

    Visual servoing technology has high potential in many industrial applications.Conventionally,precise servoing is often achieved by using high-resolution cameras which are usually costly and unaffordable in many of industrial scenarios.A novel visual servoing control scheme which generates robot control signal based on the fusion of visual feedback and robot motion feedback was presented in the paper.By doing so,the robot control loop runs at a frequency independent to the visual feedback frequency (i.e.the frame rate of a camera).Therefore,it becomes feasible to achieve precise and dynamic servoing even with a low frame rate and low-cost camera.The new visual servoing scheme was introduced briefly.The feasibility of the scheme as well as its performances in low frame rate conditions was also illustrated experimentally.

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    Quantum blockchain:can blockchain integrated with quantum information technology resist quantum supremacy?
    Jun ZHANG,Yong YUAN,Xiao WANG,Fei-Yue WANG
    Chinese Journal of Intelligent Science and Technology    2019, 1 (4): 409-414.   DOI: 10.11959/j.issn.2096-6652.201945
    Abstract369)   HTML29)    PDF(pc) (653KB)(326)       Save

    Quantum computers,which substantially exceed traditional computing speed and data processing capacity,are gradually moving from theory toward practice.The tremendous computing power of quantum computers will bring fundamental challenges to current information encryption mechanism.Two key applications of quantum information technology were introduced,followed by comments on how quantum supremacy threatens the current blockchain consensus and encryption mechanisms.Meanwhile,considering loopholes existing in the current blockchain technology,a blockchain system integrating quantum technology was discussed aiming to prevent the threat of quantum supremacy.

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    Transparent farm based on blockchain technology
    Xiujuan WANG,Jing HUA,Mengzhen KANG,Haoyu WANG,Yong YUAN,Fei-Yue WANG
    Chinese Journal of Intelligent Science and Technology    2019, 1 (4): 400-408.   DOI: 10.11959/j.issn.2096-6652.201944
    Abstract207)   HTML41)    PDF(pc) (3420KB)(322)       Save

    With the development of new types of agricultural business mode,consumers can send orders remotely to the growers,in order to satisfy their high requirements for the safety of agricultural products.In addition to consumers and growers,stakeholders of agricultural supply chain include farm managers,agricultural input suppliers,agricultural knowledge suppliers and third-party regulators and financial service providers.Therefore,how to build a trustworthy community,to protect the benefit of all parties and achieve sustainable development are challenges that are faced by new farming business mode.For farm managing mode with multiple stakeholders,smart contracts provide a credit guarantee mechanism.An online farm platform based on smart contracts,which constructs a trustworthy community corresponding to the offline one with blockchain technology was proposed in this paper.Differing from traditional traceability systems,the characteristics of the decentralized data management and non-tamper ability were utilized,and the authenticity of data through the mutual verification could be ensured.These methods increase the cost of data fraud,and thus achieve a trustworthy agricultural community.This work aims at ensuring the data validity in Internet+ agriculture,and supporting the orderly sustainable development of emerging agricultural management mode.

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    Study on path planning of unmanned surface vessel based on data-driven genetic algorithm
    Junfeng XIN,Yongbo ZHANG,Jiageng BO,Bowen ZHAO,Shiyuan FAN
    Chinese Journal of Intelligent Science and Technology    2019, 1 (2): 171-180.   DOI: 10.11959/j.issn.2096-6652.201926
    Abstract470)   HTML17)    PDF(pc) (5173KB)(318)       Save

    The genetic algorithm (GA) is an effective method for the path planning system of unmanned surface vessel (USV),but it is easy to fall into local optimal precocity and converges slowly.For this,without increasing the complexity of the algorithm,a data-driven linear changing parameters genetic algorithm (LCPGA) was proposed,which can adjust adaptively control parameters in the shortest time.Compared with the traditional genetic algorithm,the LCPGA increases the diversity of the population,avoids falling into local optimum more effectively,and improves the accuracy,robustness and convergence speed of path planning.Then simulation experiments and field tests verify the more excellent performance of the LCPGA.This algorithm can be helpful in path planning for unmanned surface vessel.

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