计算机应用 ›› 2013, Vol. 33 ›› Issue (10): 2811-2814.

• 人工智能 • 上一篇    下一篇

基于模糊粗糙集和D-S证据理论的多源灌溉信息融合方法

陈智芳,王景雷,孙景生,刘祖贵,宋妮,高阳   

  1. 农业部作物需水与调控重点开放实验室(中国农业科学院农田灌溉研究所),河南 新乡 453002
  • 收稿日期:2013-04-27 修回日期:2013-06-13 出版日期:2013-10-01 发布日期:2013-11-01
  • 通讯作者: 王景雷
  • 作者简介:陈智芳(1981-),女,河南新乡人,助理研究员,博士研究生,主要研究方向:计算机在农业水资源高效利用中的应用;王景雷(1972-),男,河南开封人,研究员,硕士,主要研究方向:节水灌溉及作物用水要素的空间变异性;孙景生(1963-),男,辽宁朝阳人,研究员,博士生导师,博士,主要研究方向:节水灌溉原理、农业水资源高效利用;刘祖贵(1963-),男,四川资阳人,副研究员,主要研究方向:作物灌溉原理、农艺节水;宋妮(1979-),女,陕西西安人,助理研究员,硕士, 主要研究方向:节水灌溉原理;高阳(1978-),男,内蒙古赤峰人,副研究员,博士,主要研究方向:作物高效用水。
  • 基金资助:
    国家自然科学基金资助项目;国家863计划项目;现代农业产业技术体系建设专项资金资助项目;农业部作物需水与调控重点开放实验室基金资助项目

Multi-source irrigation information fusion method based on fuzzy rough set and D-S evidence theory

CHEN Zhifang,WANG Jinglei,SUN Jingsheng,LIU Zhugui,SONG Ni,GAO Yang   

  1. Key Laboratory for Crop Water Requirement and Regulation, Ministry of Agriculture, (Farmland Irrigation Research Institute of Chinese Academy of Agricultural Sciences), Xinxiang Henan 453002,China
  • Received:2013-04-27 Revised:2013-06-13 Online:2013-11-01 Published:2013-10-01
  • Contact: WANG Jinglei

摘要: 针对多源灌溉信息决策过程中不确定性信息难以融合的问题,提出了一种基于模糊粗糙集和D-S证据理论相结合的决策融合方法。运用模糊粗糙集理论,建立基本概率分配函数,计算各灌溉因子与灌溉决策之间的依赖程度,构建多个融合灌溉因子对灌溉决策的识别框架;然后运用改进的D-S证据理论,进行多源灌溉信息决策层级的融合,最终解决不确定信息的表达和合成问题。应用上述方法对华北地区冬小麦土壤水分、光合速率和气孔导度等信息进行灌溉决策融合,结果显示:灌溉决策的不确定性由融合前的最高38%降至9.84%,该方法可有效地提高灌溉决策精度,降低灌溉决策的不确定性

关键词: 模糊粗糙集, 不确定性信息, D-S证据理论, 多源信息融合, 权重系数

Abstract: Concerning the problem that uncertainty information is difficult to be merged during the decision-making process of multi-source irrigation information, a decision fusion method based on fuzzy rough set and Dempster-Shafer (D-S) evidence theory was proposed. Using the fuzzy rough set theory,the basic probability distribution function was established, the interdependence between irrigation factors and irrigation decision was calculated, and the identification framework of irrigation decision on the multiple fusion irrigation factors was built. Using the improved D-S evidence theory, the multi-source irrigation information was fused at the decision-making level, the expression and synthesis problems of uncertain information were solved. The information of winter wheat such as soil moisture, photosynthetic rate and stomatal conductance in north China was fused in irrigation decision by the application of the methods mentioned above. The results show that the uncertainty of the irrigation decision decreases from 38.0% before fusion to 9.84%. The method can effectively improve the accuracy of irrigation decision and reduce the uncertainty of the irrigation decision.

Key words: fuzzy rough set, uncertain information, Dempster-Shafer (D-S) evidential theory, multi-source information fusion, weight coefficient

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