作　　者： (祝秀信）;

机构地区： 云南省水文水资源局文山分局,云南文山663000

出　　处： 《水资源与水工程学报》 2017年第3期91-97,104,共8页

摘　　要： 从生命安全、经济安全、社会安全和生态安全4个方面选取20个指标构建区域水安全动态评价指标体系和分级标准。利用自治粒子群优化(AGPSO)算法寻优最大熵投影寻踪(MEPP)技术最佳投影方向,提出AGPSOMEPP水安全评价模型,并分别构建加速粒子群优化(APSO)算法、惯性权重线性递减粒子群优化(LDWPSO)算法和基本粒子群优化(PSO)算法-MEPP模型作对比模型对云南省2006-2015年及2020年水安全进行评价。结果表明:AGPSO寻优MEPP目标函数获得的最优值、最差值、平均值和标准差均优于APSO、LDWPSO和PSO算法,具有较好的全局极值寻优能力;AGPSO-MEPP模型对云南省2006-2013年水安全评价为"不安全",2014-2015年评价为"基本安全",2020年评价为"安全"。2006-2015年的10年间云南省水安全随时间呈提升趋势,且提升趋势显著;AGPSO-MEPP模型对云南省水安全评价结果与APSO-MEPP模型相同,但在排序上存在差异;与LDWPSO-MEPP、PSO-MEPP模型在评价结果及排序上均存在差异。其中,与PSO-MEPP模型的评价及排序结果差异最为显著,表明算法的极值寻优能力决定着评价精度的高低。 In view of life safety, economic security, social security and ecological security, 20 indicators were selected to construct regional water security dynamic evaluation index system and grading standard. The AGPSO -MEPP is proposed to optimize the projection direction of the maximum entropy projection pursuit （MEPP）, and the AGPSO -MEPP water safety evaluation model is proposed. The APSO algo- rithm is constructed and the inertia weight is linearly reduced. Particle Swarm Optimization （LDWPSO） algorithm and Basic Particle Swarm Optimization （PSO） - MEPP model were used to evaluate the water security of Yunnan Province from 2006 to 2015 and 2020. The results show that： The optimal, worst - case, average and standard deviation of objective function of AGPSO were better than those of APSO, LDWPSO and PSO, and had the best global optimum. The water security assessment of Yunnan Province from 2006 to 2013 was ＂unsafe＂ by the AGPSO -MEPP model, ＂almost safe ＂ from 2014 to 2015, and ＂safe ＂ in 2020. From 2006 to 2015, the water security of Yunnan Province showed an increasing trend with time, and the upgrading trend was remarkable. The water security evaluation results of APSAP - MEPP model are the same as those of APSO - MEPP model, but the rankings are different. There are differences in the evaluation results and ranking with LDWPSO - MEPP and PSO - MEPP models. Among them, the difference between PSO - MEPP model and the ranking of PSO - MEPP model is the most sig-nificant, which indicates that the extreme value optimization ability of the algorithm determines the accu- racy of evaluation.

关 键 词： 水安全 最大熵投影寻踪 指标体系 自治粒子群优化算法 加速粒子群优化算法 惯性权重线性递减粒子群优化算法 粒子群优化算法 云南省