DocumentCode :
1811421
Title :
The research of rainfall prediction models based on Matlab neural network
Author :
Gan, Xianggen ; Chen, Lihong ; Yang, Dongbao ; Liu, Guang
Author_Institution :
Jiangxi Vocational & Tech. Coll. of Inf. Applic., Nanchang, China
fYear :
2011
fDate :
15-17 Sept. 2011
Firstpage :
45
Lastpage :
48
Abstract :
The continuously cloudy or rainy forecast is an important basis that is used to make choice of wheat harvest time but multiple regression weather forecast models hardly content the rate of required accuracy. Matlab neural network toolbox is composed of a series of typical neural network activation functions that make computing network output into calling activation functions. BP artificial neural network that is based on Matlab platform and utilizes error back propagation algorithm to revise network weight has dynamic frame characteristics and is convenient for constructing network and programming. After it has been trained by input forecast samples, network forecast model that has three neural cells possesses very good generalization capability. After we contrast fitting rate and accuracy rate of network model with ones of regression model, network model has a distinct advantage over regression model.
Keywords :
backpropagation; crops; generalisation (artificial intelligence); geophysics computing; mathematics computing; neural nets; rain; weather forecasting; BP artificial neural network; Matlab neural network toolbox; accuracy rate; continuously cloudy forecasting; continuously rainy forecasting; dynamic frame characteristics; error back propagation algorithm; fitting rate; generalization capability; neural cells; neural network activation function; rainfall prediction model; regression weather forecast model; wheat harvest time; Accuracy; Fitting; Mathematical model; Predictive models; Training; Weather forecasting; BP network; forecast models; learning algorithm; network training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cloud Computing and Intelligence Systems (CCIS), 2011 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-61284-203-5
Type :
conf
DOI :
10.1109/CCIS.2011.6045029
Filename :
6045029
Link To Document :
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