中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Prediction of winter wheat evapotranspiration based on BP neural networks

文献类型:期刊论文

作者Chen, Bo(陈博) ; Ouyang, Zhu
刊名Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering
出版日期2010
卷号26期号:4页码:81-86
关键词Backpropagation Crops Evapotranspiration Forecasting Geologic models Meteorology Soil moisture Speech recognition Underwater soils Water content Water supply
通讯作者Ouyang, Zhu
英文摘要By adopting meteorological data and the data from 2003 to 2006 collected from large weighing lysimeter with the crop of winter wheat at Yucheng Comprehensive Experimental Station, Chinese Academy of Sciences, a predicted model for winter wheat evapotranspiration was developed. Based on BP neural network, the model performance was tested with inputs of daily maximum temperature, net radiation, soil water content of top 60 cm layer, date number and measured crop coefficient and output of observed evaportranspiration. The topology of the neural network was 5-9-1 and the training function was Trainbr. The results showed that the model was good in simulating water consumption of winter wheat with average relative error of 13.1%, standard error of 0.88 mm, and Nash-Sutcliffe efficiency coefficient of 0.865. And the model can meet the requiements of production.
收录类别EI
语种中文
公开日期2012-05-29
源URL[http://ir.igsnrr.ac.cn/handle/311030/21940]  
专题地理科学与资源研究所_研究生部
推荐引用方式
GB/T 7714
Chen, Bo,Ouyang, Zhu. Prediction of winter wheat evapotranspiration based on BP neural networks[J]. Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering,2010,26(4):81-86.
APA Chen, Bo,&Ouyang, Zhu.(2010).Prediction of winter wheat evapotranspiration based on BP neural networks.Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering,26(4),81-86.
MLA Chen, Bo,et al."Prediction of winter wheat evapotranspiration based on BP neural networks".Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering 26.4(2010):81-86.

入库方式: OAI收割

来源:地理科学与资源研究所

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