干旱地区农业研究2013，Vol.31Issue(2)：209-213,224,6.
基于W-F定律和PNN模型的西安市潜水脆弱性评价
Unconfined water vulnerability evaluation based on Weber-Fechner law and Probabilistic Neural Network
摘要
Abstract
As the present groundwater vulnerability evaluation methods were more subjective, and could not evaluate the vulnerability of water quantity, this paper combined the Weber-Fechner expand law (a psychophysics' principle) and Probabilistic Neural Network to put forward a new groundwater vulnerability evaluation method-W-F and PNN method, which could evaluate the quality and quantity vulnerability of groundwater. The new method was used to evaluate the un-confined water quality and quantity vulnerability of Xi' an for the year 2005. The result shows that the W-F and PNN method can avoid the influence of subjection and limitation of traditional methods, the evaluation result was reasonable and reliable, and the method has wider evaluation scope and was valuable to be widely used.关键词
W-F拓广定律/概率神经网络/潜水/水质/水量/地下水脆弱性评价Key words
Weber-Fechner expand law/ Probabilistic Neural Network/ unconfined water/ water quality/ water quantity/ groundwater vulnerability evaluation分类
天文与地球科学引用本文复制引用
董艳慧,周维博,赵平歌..基于W-F定律和PNN模型的西安市潜水脆弱性评价[J].干旱地区农业研究,2013,31(2):209-213,224,6.基金项目
西安工业大学校长科研基金(XAGDXJJ1123) （XAGDXJJ1123）
西安市水务局资助项目 （）
