摘要
基于尊重现状和效率原则,选取水资源开发用率、总人口等11个指标构建云南省水量分配指标体系和水量分配投影寻踪(PP)模型.利用灰狼优化(GWO)算法搜寻PP模型最佳投影方向,构建GWO-PP水量分配模型对云南省16个州(市)水量进行分配.并通过4个典型测试函数对GWO算法进行仿真验证,仿真结果与文化算法(CA)、萤火虫算法(FA)和粒子群优化(PSO)算法进行对比.结果表明:GWO算法寻优效果优于CA、FA和PSO算法,具有收敛速度快、寻优精度高和全局寻优能力强等特点.GWO-PP模型水量分配结果较综合法水量分配结果更科学客观.模型及方法具有一定的可操作性和有效性,可为水量分配提供新的途径和方法.
Based on respect for the status quo and the principle of efficiency, water resources development with selecting rate, the total population of 11 indicators and other metrics to build Yunnan water allocation and water allocation system projection pursuit （PP） model. Utilization of gray optimization （GWO） algorith- mic search PP model best projection direction, build GWO-PP water allocation model in Yunnan 16 states （cities） of water for distribution. And by four typical test function GWO algorithm simulation, the simulation results and Cultural algorithm （CA）, firefly algorithm （FA） and particle swarm optimization（PSO） are com- pared. The results show that：GWO is better than CA, FA and PSO~ it has good convergence speed, high precision and optimization of strong global optimization ability; GWO-PP water allocation results are more scientific and objective than ones of the integrated water allocaiton method. Models and methods have certain operability and effectiveness, so as to provide new ways and means for the water allocation.
作者
陈金红
程刚
Chen Jinhong Cheng Gang(Yunnan Institute of Water ＆ Hydropower Engineering Investigation, Design ＆ Research, Kunming 650021, China)
出处
《三峡大学学报（自然科学版）》
CAS
2016年第5期29-35,共7页
Journal of China Three Gorges University：Natural Sciences
基金
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)
关键词
水量分配
指标体系
灰狼算法
投影寻踪
water allocation
index system
gray wolf optimization algorithm
projection pursuit
