DocumentCode :
588911
Title :
The PCA-BP Neural Network Model of Evaluating Integration Degree of Chinese Logistics and Manufacturing
Author :
Junjuan Zhong
Author_Institution :
Ba-fang Logistics Coll., Fuzhou Univ., Fuzhou, China
Volume :
2
fYear :
2012
fDate :
28-29 Oct. 2012
Firstpage :
206
Lastpage :
209
Abstract :
This paper uses principal component analysis(PCA)-BP neural network model to evaluate the degree of the logistics industry and manufacturing integration, for more complex indicator system on the retention of the large number of indicators of information. The evaluation results demonstrate that the effectiveness of the evaluation models and methods.
Keywords :
backpropagation; logistics; manufacturing industries; neural nets; principal component analysis; production engineering computing; service industries; Chinese logistics integration degree; Chinese manufacturing integration degree; PCA-BP neural network; backpropagation; information indicator; logistics industry; principal component analysis; Couplings; Industries; Logistics; Neural networks; Principal component analysis; Training; BP neural network; Degree of industry integration; Evaluate; principal component analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Design (ISCID), 2012 Fifth International Symposium on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-2646-9
Type :
conf
DOI :
10.1109/ISCID.2012.203
Filename :
6405966
Link To Document :
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