干旱地区农业研究2013，Vol.31Issue(1)：188-192,198,6.
基于T-S模糊神经网络的民勤地下水水质综合评价
Comprehensive assessment of groundwater quality in Minqin Basin based on T-S Fuzzy Neural Network
摘要
Abstract
In order to find out the variation of groundwater quality of Minqin basin in Shiyang River Valley in recent 25 years and to provide the decision-making reference for rational exploitation of local water resources and eco-environ-mental protection, T - S Fuzzy Neural Network model was applied to the comprehensive assessment of groundwater quality in the year of 1983, 1990, 2000 and 2008, and the Support Vector Machines (SVM) model was applied to test the results . The results showed that the overall groundwater quality of Minqin Basin was poor and it was overall better in the southern region than in the northern region. Except for the area surrounding Hongyashan reservoir, the groundwater quality of more than 80% regions was poorly achieved grade V . The groundwater quality of partial wells at the edge of deserts, such as No. 141, 147, 156 and 168, showed a improving trend. The results of the two models were generally concordant, but the T- S Fuzzy Neural Network model exhibited a fast convergence, therefore it can be effectively applied to the comprehensive assessment of groundwater quality.关键词
T-S模糊神经网络/支持向量机/地下水水质评价/民勤盆地Key words
T - S Fuzzy Neural Network model/ Support Vector Machines/ groundwater quality assessment/ Minqin Basin分类
天文与地球科学引用本文复制引用
汪新波,粟晓玲..基于T-S模糊神经网络的民勤地下水水质综合评价[J].干旱地区农业研究,2013,31(1):188-192,198,6.基金项目
国家自然科学基金项目(50879071) （50879071）
西北农林科技大学基本科研业务费科技创新重点项目(QN201168) （QN201168）
