摘要
建立了基于混沌优化算法的模糊神经网络评价模型。与单纯的模糊人工神经网络评价模型相比,具有更快的计算速度、更高的计算精度及更好的评价效果,同时该方法还具有良好的聚类效果。应用该模型对黑龙江省三江平原地下水脆弱性进行了评价,评价结果与前人评价结果相互吻合,可以为有关决策部门采取相应的措施以降低环境风险提供参考。
A fuzzy neural network evaluation model based on chaos optimization algorithm was established.Compared with the traditional fuzzy artificial neural network evaluation model,the model has higher accuracy,faster speed and better effect of evaluation,at the same time,the method also had a good effect of clustering.Using the model,g roundw ater vulnerability evalation has been done for the six dist ricts of Sanjiang Plain.The ev aluation result w as conformity with the previous,for the rele v ant decisionr making depa rtments to take corres ponding measures to provide the reference to reduce environmental risk.
作者
盖兆梅
刘仁涛
付强
姜秋香
GAI Zhaomei;LIU Rentao;FU Qiang;JIANG Qiuxiang(College of Water Conservancy and Architecture,Northeast Agricultural University,Harbin 150030,China;School of Municipal Engineering Technology,Heilongjiang Collage of Construction,Harbin 150025,China)
出处
《南水北调与水利科技》
CSCD
北大核心
2018年第S01期1-4,共4页
South-to-North Water Transfers and Water Science & Technology
基金
国家自然科学基金(51679040)
黑龙江省自然科学基金(E2016004)。
关键词
地下水脆弱性
评价
混沌优化算法
模糊人工神经网络
groundwater vulnerability
evaluation
chaos optimization algorithm
fuzzy art ifical neural network
