水土保持研究2013，Vol.20Issue(2)：25-28,4.
基于RBF神经网络的土壤侵蚀预测模型研究
Research on Soil Erosion Prediction Model Based on RBF Neural Network
摘要
Abstract
The physical mechanism of soil erosion is so complicated that it is difficult to be described by the mathematical mode. According to the characteristic of vagueness, randomness and nonlinear of soil erosion process, the RBF neural network theory and method are applied to soil erosion prediction. With Xingmu small watershed as the research case, the application of RBF neural network method was adopted to construct soil erosion prediction model, and flood season rainfall, runoff coefficient, soil capacity, organic matter content and porosity and so on were used as input layer variables, and yearly soil erosion modulus were used as the output layer variable. Through the simulation training and the forecast, results obtained through RBF neural network were precise, RBF neural network could be used as soil erosion prediction model, compared with the traditional BP neural network, RBF neural network could give the higher accuracy prediction results. RBF neural network model shifts soil erosion prediction problem into the impact factor and erosion modulus nonlinear problem, the model of the simulation and forecast provides a new way to complex law of soil erosion research.关键词
土壤侵蚀预测/RBF神经网络/BP神经网络/预测模型Key words
soil erosion prediction/ RBF neural network/ BP neural network/ prediction mode分类
农业科技引用本文复制引用
伊燕平,卢文喜,许晓鸿,洪德法..基于RBF神经网络的土壤侵蚀预测模型研究[J].水土保持研究,2013,20(2):25-28,4.基金项目
国家自然科学基金资助项目(41072171) （41072171）
水利部"948"计划项目(201122) （201122）
