NDLI: Evaluation of knowledge complementary degree for creative industry cluster based on BP neural networks

Content Provider	IEEE Xplore Digital Library
Author	Li Yu-hua Tan Jin yan Hu Yao-ying
Copyright Year	2011
Description	Author affiliation: College of Management, Harbin University of Science Technology, P.R. China, 150040 (Li Yu-hua; Tan Jin yan; Hu Yao-ying)
Abstract	Creative industries are intelligent, highly knowledgeable. Cluster model increasingly becomes the main economic organization form of the world creative industry. Getting complementary knowledge and realizing the knowledge complementary within creative industry cluster is the main motivation of each cooperator. What's more, the complementary degree of knowledge also determines the development altitude of creative industry cluster. So, the BP neural network model was applied to evaluate the degree of knowledge complementary within the creative industry cluster. This paper constructs the creative industry cluster evaluation index system of knowledge complementary degree. Simultaneously, the paper has proposed the method to evaluate the creative industry cluster knowledge complementary degree based on BP Neural Networks. The study indicates that BP neural network is a model without linear mapping. It can give a satisfactory effort while the indices with a high level of correlation, nonlinear changing and data lacking. So, it's a relatively optimum method used for forecasting, with wide applying area and high value of popularizing.
Starting Page	41
Ending Page	46
File Size	148299
Page Count	6
File Format	PDF
ISBN	9781457718854
ISSN	21551855
e-ISBN	9781457718885
DOI	10.1109/ICMSE.2011.6069940
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-13
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Industries Knowledge engineering Training knowledge complementary degree creative industry cluster Neurons Neural networks Receivers evaluation index BP neural networks Indexes
Content Type	Text
Resource Type	Article

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