Calibration Study of Moisture Production Parameters Model Based on Neural Network by LM Algorithm

摘要：

The is a kind of effective method of water-saving irrigation. Crop moisture production parameters model provide relationship between the output and the evapotranspiration. The article Using improved BP neural network based LM algorithm calibrate Jensen model, and solve moisture sensitivity by test results of winter wheat moisture production parameters in Shanxi Province Xiaohe area. Using this method to solve moisture sensitivity has higher precision and can provide technical guidance to inadequately irrigation.

关键词： LM algorithm Jensen model moisture sensitivity

作者: Liu Ling Zhao Yong-zhi Wang Lei Wang Yang-ren

作者单位: Tanjin Agricultural University,hydraulic engineering department,Tianjin,China Tanjin Agricultural University,hydraulic engineering department,TtanjnChina Tanjin Agricultural University,senior profession institute,tianjin,China

会议类型: 国际会议

会议名称: 2011 International Conference on Agricultural Engineering New Technology & Taishan Academic Forum(2011农业工程新技术国际学术会议暨泰山学术论坛 ICAE2011&TSAF)

会议地点: 山东淄博

会议语种:英文

页码: 600-604

在线出版日期: 2011-05-27（万方平台首次上网日期，不代表论文的发表时间）