水资源与水工程学报2017，Vol.28Issue(5)：80-86,7.DOI:10.11705/j.issn.1672-643X.2017.05.14
基于磷虾觅食算法-最大熵投影寻踪模型的区域水安全评价
Regional water security evaluation based on krill herd algorithm-maximum entropy projection pursuit model
摘要
Abstract
According to 12 indicators selected from three aspects of the total red line,the efficiency of the red line,accept the red line, the regional water safety evaluation index system and grading standards were built under the most stringent water resources management constraints.Krill foraging algorithm (KH)-Maximum Entropy Projection Pursuit(MEPP)water security evaluation was proposed,and Ar-tificial Bee Colony(ABC)algorithm,cultural algorithm(CA)were constructed to compare with the par-ticle swarm optimization(PSO)algorithm -MEPP evaluation model.A case study on water security of 16 administrative regions in Yunnan Province was carried out.The results show that the optimization ac-curacy of KH algorithm is better than that of ABC,CA and PSO algorithm,and has good global extremum search ability.The KH -MEPP model evaluates the water security of Diqing, Dehong, Nujiang and Xishuangbanna as safe,and Lijiang is evaluated as"unsafe".The rest of the administrative regions are rated as"basically safe".The results of the KH -MEPP model are the same as those of the PSO -MEPP model in Yunnan Province,but there are differences in the sorting.The results of CA-MEPP and ABC-MEPP are different in the evaluation results and ranking.关键词
水安全/最大熵投影寻踪/指标体系/磷虾觅食算法/人工蜂群算法/文化算法/粒子群优化算法/云南省Key words
water security/maximum entropy projection pursuit/index system/krill herd algorithm/artifi-cial bee colony algorithm/cultural algorithm/particle swarm optimization algorithm/Yunnan Province分类
建筑与水利引用本文复制引用
王应武,陈栋格..基于磷虾觅食算法-最大熵投影寻踪模型的区域水安全评价[J].水资源与水工程学报,2017,28(5):80-86,7.基金项目
国家水体污染控制与治理科技重大专项(201307102-006-01),院士工作站建设专项(2015IC013) （201307102-006-01）
