Artificial neural network model for soil moisture forecast in deficit irrigation rice field

被引：0
|
作者：
Zhou, MY [1 ]
Chen, HW [1 ]
机构：
[1] Yangzhou Univ, Coll Hydraul Sci & Engn, Yangzhou 225009, Peoples R China
来源：
Land and Water Management: Decision Tools and Practices, Vols 1 and 2 | 2004年
关键词：
deficit irrigation; rice field; soil moisture forecast; artificial neural network;
D O I：
暂无
中图分类号：
S2 [农业工程];
学科分类号：
0828 ;
摘要：
There is a complex nonlinear relation between soil moisture and precipitation, irrigation, evapotranspiration, root Zone lower bounds, etc. It causes the changing rule of soil moisture very complex. Based on analyses of artificial neural network theories, this paper set up a BP model that describes soil moisture change of limited irrigation rice zone. The packets in the soil water forecast are compared with the packets in the observations. Research indicates the BP network can be used in the regional soil moisture forecast. The method has the characteristics of simplicity, feasibility and high accuracy.
引用
收藏
页码：96 / 100
页数：5
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