A forecasting method based on principal component analysis and fuzzy neural network for forest ecological product benefits

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作者：
机构：
[1] [1,Xiao, Nanyun
[2] Jia, Li
来源：
Jia, Li (xiaonanyun@sina.com) | 1600年 / Universidad Central de Venezuela卷 / 55期
关键词：
Ecology - Forestry - Fuzzy inference - Forecasting - Fuzzy neural networks;
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摘要：
This paper proposes a forecasting method based on Fuzzy Neural Network integrating with Principal Component Analysis to predict forest ecological benefits. This method makes use of the characteristics of fuzzy neural network, which has the advantages of neural network and fuzzy theory, to obtain effective prediction, and puts forward to use the method of Principal Component Analysis (PCA) method to reduce the dimensionality of the evaluation factors. The features chosen by PCA are chosen as the input of fuzzy neural network, and the fuzzy neural network is used as the prediction model. In this paper, the validity of this method is verified by the data of China Statistical yearbook.
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