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