Title :
Calibration study of moisture production parameters model based on neural network by LM algorithm
Author :
Ling, Liu ; Yong-zhi, Zhao ; Lei, Wang ; Yang-ren, Wang
Author_Institution :
Hydraulic Eng. Dept., Tanjin Agric. Univ., Tianjin, China
Abstract :
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.
Keywords :
backpropagation; crops; evaporation; irrigation; moisture; neural nets; transpiration; water conservation; BP neural network; Jensen model; LM algorithm; Shanxi Province Xiaohe area; calibration study; crop moisture production parameter model; evapotranspiration; moisture sensitivity; water-saving irrigation; winter wheat moisture production parameters; Data models; Indexes; Irrigation; Mathematical model; Moisture; Production; Jensen model; LM algorithm; moisture sensitivity;
Conference_Titel :
New Technology of Agricultural Engineering (ICAE), 2011 International Conference on
Conference_Location :
Zibo
Print_ISBN :
978-1-4244-9574-0
DOI :
10.1109/ICAE.2011.5943868
