DocumentCode :
1790867
Title :
A Neural Network Approach to Evaluate Agility of Cloud-Based Virtual Enterprise
Author :
Miao Ning ; Chen Jun ; Pei Shengli
Author_Institution :
Dept. of Comput. Sci., Tianjin Univ. of Finance & Econ., Tianjin, China
fYear :
2014
fDate :
25-26 Oct. 2014
Firstpage :
28
Lastpage :
31
Abstract :
As a new mode of Internet applications, cloud computing will become the future access to the dominant way of services and information. In cloud computing environment is more suitable for virtual enterprise, it is more powerful. In order to study how to measure Agility of Cloud-based Virtual Enterprise (CVE), the relationship between CVE and its member is analyzed first. Base on it, a new method using Bayesian Regularized Neural Network (BRNN) for Agility Evaluation of Virtual Enterprise is developed. A simulative example illustrates the usefulness of the proposed method. In contrast to the standard BP neural network, the result shows that BRNN overcome the over-fitting problems, it can be used to measure any size of CVE.
Keywords :
Bayes methods; backpropagation; cloud computing; neural nets; virtual enterprises; BP neural network approach; BRNN; Bayesian regularized neural network; CVE; Internet; agility evaluation; cloud computing environment; cloud-based virtual enterprise; Bayes methods; Cloud computing; Companies; Neural networks; Training; Virtual enterprises; BP neural network; Bayesian regularization; LT codes; agile evaluation; member; virtual enterprise;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2014 7th International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-6635-6
Type :
conf
DOI :
10.1109/ICICTA.2014.14
Filename :
7003477
Link To Document :
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