Chinese Journal of Intelligent Science and Technology ›› 2021, Vol. 3 ›› Issue (4): 499-506.doi: 10.11959/j.issn.2096-6652.202150

• Papers and Reports • Previous Articles     Next Articles

Windblown sand control decision-making support system based on parallel intelligence: Taklimakan desert highway and its sand-breaking system

Fangle CHANG1,2, Mengzhen KANG1,3, Xiujuan WANG1,3, Jiaqiang LEI4, Fei-Yue WANG1,3,5   

  1. 1 The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
    2 Ningbo Research Institute, Zhejiang University, Ningbo 315000, China
    3 Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
    4 Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
    5 School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
  • Revised:2021-02-04 Online:2021-12-15 Published:2021-12-01
  • Supported by:
    The Strategic Priority Research Program of the Chinese Academy of Sciences(XDA20030102);Chinese Academy of Sciences-Thailand National Science and Technology Development Agency Joint Research Program(GJHZ2076)


Using Taklimakan desert highway and its sand-breaking system as the research object for complex system management and control, the ACP-based parallel intelligence theory to deal with the problems of the difficulty in modeling, analyzing, and predicting of sand-breaking system was applied, to realize the intelligent decision support for sand-breaking system management and control, support the sustainable development of aeolian environment.The expert experience knowledge to construct the artificial desert highway sand-breaking system was extracted by simulating physical process.The sand-control efficiency index of the artificial system was calculated using equations, then evaluated and modified by comparing and learning with the actual system.Using parallel intelligent theory, the artificial system and the actual system can learn from each other to provide decision support for sand control.

Key words: parallel intelligence, computational experiment, desert highway sand-breaking system, decision support

CLC Number: 

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