| 参考作物腾发量预测的径向基函数法 |
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| 引用本文： | 顾世祥,王士武,袁宏源.参考作物腾发量预测的径向基函数法[J].水科学进展,1999,10(2):123-128. |
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| 作者姓名： | 顾世祥 王士武 袁宏源 |
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| 作者单位： | 1.武汉水利电力大学水利工程系 武汉430072; |
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| 基金项目： | “九五”国家重点科技攻关项目(96-006-02-05-02) |
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| 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。
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| 关 键 词： | 参考作物腾发量 数字试验 预测 神经网络 径向基函数法 |
| 收稿时间： | 1997-12-23 |
| 修稿时间： | 1997-12-23 |
A Radial Basis Function
Model Predicting |
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| Gu Shixiang.A Radial Basis Function
Model Predicting[J].Advances in Water Science,1999,10(2):123-128. |
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| Authors: | Gu Shixiang |
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| Institution: | 1.Wuhan University of Hydraulic and Electric Engineering, Wuhan 430072;2.Helongjiang Hydraulic College, Haerbing 150086 |
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| Abstract: | 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. |
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| Keywords: | reference evaportranspiration digital experiment forecast artificial neural network radial basis function model |
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