大数据 ›› 2018, Vol. 4 ›› Issue (6): 54-64.doi: 10.11959/j.issn.2096-0271.2018061

• 研究 • 上一篇    下一篇

基于主动学习和克里金插值的空气质量推测

常慧娟1,於志文1,於志勇2,安琦1,郭斌1   

  1. 1 西北工业大学计算机学院,陕西 西安 710072
    2 福州大学数学与计算机科学学院,福建 福州 350108
  • 出版日期:2018-11-15 发布日期:2019-01-11
  • 基金资助:
    国家杰出青年科学基金资助项目;国家重点研发计划基金资助项目;国家自然科学基金资助项目

Air quality estimation based on active learning and Kriging interpolation

Huijuan CHANG1,Zhiwen YU1,Zhiyong YU2,Qi AN1,Bin GUO1   

  1. 1 School of Computer Science,Northwestern Polytechnical University,Xi’an 710072,China
    2 College of Mathematics and Computer Science,Fuzhou University,Fuzhou 350108,China
  • Online:2018-11-15 Published:2019-01-11
  • Supported by:
    The National Science Fund for Distinguished Young Scholars;The National Key Research and Development Program of China;The National Natural Science Foundation of China

摘要:

空气质量监测站仅能在少数位置部署,故而无法获取城市中每个位置的空气质量信息。提出了一种基于主动学习和克里金插值的空气质量推测算法。该算法首先选用克里金插值作为基础的空气质量推测算法,然后结合主动学习的思想,对置信度最大的位置进行优先采样,最终建立基于主动学习的插值模型,通过最少的监测点对空气质量进行采样,最大限度地提升推测其他位置空气质量的准确度。研究结果表明,所提算法能够有效地提高空气质量推测精度,同时减少监测站采样数量,降低部署成本。

关键词: 克里金插值, 空气质量指数, 主动学习, 空间插值, 空气质量推测

Abstract:

For the air quality monitoring station,it can only be deployed in a few locations and cannot obtain the air quality information of each location in the city.An air quality estimation algorithm based on active learning and Kriging interpolation was proposed.Firstly,Kriging interpolation was used as the basic air quality estimation algorithm.Secondly,combined with the idea of active learning,the position-first sampling with the highest confidence of the model was searched.Finally,an interpolation model based on active learning was established to select the least position-to-air quality.Sampling was performed to maximize the accuracy of air quality at other locations.The results show that the proposed algorithm can effectively improve the accuracy of air quality estimation,reduce the number of sampling stations and reduce the deployment cost.

Key words: Kriging interpolation, air quality index, active learning, spatial interpolation, air quality estimation

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