摘要
探讨了采用径向基函数网络模型进行参考作物腾发量预测方法的可行性，设计多组数字实验处理研究了输入因子间相关性对网络模型预测准确性的影响，预测结果与Ｐｅｎｍａｎ－Ｍｏｎｔｉｅｔｈ方法计算结果比较表明，所确定的模型与改进的Ｐｅｎｍａｎ公式计算值有很高的一致性，具有一定精度。
To discuss the feasibility of utilizing the radial basis function artificial neural network (RBF ANN) model and to predict daily reference evaportranspiration,five different kinds of model inputting factors’composition are made and their correlative influences on the model’s forecasting precision are studied.A case of applying the model shows that the precision of forecasting by using the RBF ANN model is high.
出处
《水科学进展》
EI
CAS
CSCD
北大核心
1999年第2期123-128,共6页
Advances in Water Science
基金
"九五"国家重点科技攻关项目
关键词
作物腾发量
试验
预测
径向基函数法
灌溉
reference evaportranspiration
digital experiment
forecast
artificial neural network
radial basis function model.
