NDLI: A Combined Forecasting Method of Grain Yield in China Based on GM(1,1) and BP Network

Content Provider	IEEE Xplore Digital Library
Author	Jian Wen Lijuan Lei
Copyright Year	2010
Abstract	In view of the fact that the system of grain yield is affected by many factors and has complicated non-linear characteristic, a combined forecasting model by using multi-indicator for grain yield in China is constructed based on BP network and grey system, which can be named GM(1, 1)–BP model. Seven index were chosen from agricultural production conditions, he primitive data of the multi-factors from 1980 to 2006 are taken as the input of BP network, The primitive data of the grain yield from 1980 to 2006 are taken as the output. Then the network structure, initial weighted values and thresholds are set. Taking the forecasting results of GM(1, 1) models for every factor from 2007 to 2015 as the input of BP network, the corresponding output of simulation are the forecasting results of the GM(1, 1)–BP model, that is the grain yield from 2007 to 2015. The data from 2007 to 2008 are used as test sets, empirical results show that the combined model has higher precision and training efficiency than the models based on GM(1, 1), BP network or GM(1, N) alone.
Starting Page	75
Ending Page	78
File Size	355931
Page Count	4
File Format	PDF
ISBN	9781424470815
e-ISBN	9781424470822
DOI	10.1109/ICIC.2010.289
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-06-04
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	BP network Artificial neural networks Predictive models Conference management Educational institutions Information management Electronic mail grain yield GM (1 Neural networks Production prediction 1) Computer networks N) Computer network management
Content Type	Text
Resource Type	Article

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