应用遗传神经网络方法分析我国降水化学数据

收集了１１１组包含Ｃａ＾２＋、Ｍｇ＾２＋等８种离子浓度和ＰＨ值的我国降水化学数据，并用遗传神经网络（Ｇｅｎｅｔｉｃ Ｎｅｕｒａｌ Ｎｅｔ－ｗｏｒｋｓ，ＧＮＮ）方法建立了这些离子浓度和ＰＨ值绵ＢＰ网络模式，运用这些模式计算了各离子浓度对ＰＨ值的贡献，结果表明，我国各地降水ＰＨ值与各地区酸性离子与碱性离子相互用途相关，其中生离子的中和作用起着主导作用。

An analysis of precipitation chemistry data in China with genetic neural network

data of precipitation chemistry in China which contained the concentrations of eight ions such as Ca 2 ,Mg 2 ,K ,Na ,NH-4 ,SO-4 {2-},NO-3 - Cl - and the pH values were collected.Based on these data,some BP neural network models that correlated the concentrations of these ions and pH values were built by genetic neural networks (GNN).By these models the contribution to the pH of each ion concentration was given out results indicated that the difference on ability for the soil particle to neutralize acidity of the precipitation is a very important reason of acid rain distribution in China.