山东农业科学2012，Vol.44Issue(12)：11-15,5.
基于BP人工神经网络的土壤含水量预测模型的研究
Study on Forecasting Model of Soft Water Content based on BP Artificial Neural Network
摘要
Abstract
Soil moisture is one of the factors restricting plant growth, so it has great significance to scientifically forecast soil moisture for making full use of soil water. In this paper, the soil moisture predicting model was put forward based on the BP neural network. The BP neural network using adaptive learning rate momentum algorithm has fast convergence rate and high error precision. According to the soil moisture forecast experiment, the BP neural network predicting model increased the convergence rate, reduced the possibility of getting into local minimum, and improved the prediction accuracy.关键词
人工神经网络/土壤含水量/预测Key words
Artificial neural network/ Soil moisture/ Prediction分类
农业科技引用本文复制引用
郭庆春,王素娟,何振芳..基于BP人工神经网络的土壤含水量预测模型的研究[J].山东农业科学,2012,44(12):11-15,5.基金项目
国家重点基础研究发展计划("973"计划)项目"季风-干旱环境系统与全球变化关系的综合集成研究"(2004CB720208) （"973"计划）
国家自然科学基金项目"轨道尺度亚洲季风机制的瞬变模拟研究"(41075067) （41075067）
