Research on Cloud Computing Industrial Cluster Innovation Evaluation Model

Yi Jie Zhuang; Min Wang; Xiao Chong Pan

doi:10.4028/www.scientific.net/AMR.711.647

Paper Titles

Development of Automatic Reinforcement Bar Placement for RC Walls Based on Structural Building Information Modeling (S-BIM)
p.623

Manufacturing Systems Integration Using Real Time QoS-Aware Middleware
p.629

A Computer Aided System to Discriminate Enhanced Colon Images by Three Data Mining Methods
p.636

New Digital Predistortion Technique with RLS Method for Wide-Band OFDM Signals
p.641

Research on Cloud Computing Industrial Cluster Innovation Evaluation Model
p.647

3D Reconstruction of Solid Rocket Motor Based on CT Images
p.652

The Swarm Intelligence Optimization Algorithm and its Application
p.659

Laboratory Management Based on Internet of Things
p.665

Human Identification Using One Lead ECG Signal
p.670

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 711Research on Cloud Computing Industrial Cluster...

Research on Cloud Computing Industrial Cluster Innovation Evaluation Model

Abstract:

In this paper, a Bayesian network-based assessment model used for evaluating the innovation of cloud computing industry is presented. Firstly, the innovation measurement model of cloud computing industrial clusters is designed. Then Bayesian network assessment and the self-learning method to the model are proposed. Finally, accompanying with empirical data, the most likely innovation status value of cloud computing industrial clusters and key variables influencing the innovation status value can be predicted. This model can provide the theory basis for researching the innovative development of cloud computing industries.

You might also be interested in these eBooks

Manufacture Engineering, Quality and Production System II

View Preview

Info:

Periodical:

Advanced Materials Research (Volume 711)

Pages:

647-651

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.711.647

Citation:

Cite this paper

Online since:

June 2013

Authors:

Yi Jie Zhuang, Min Wang, Xiao Chong Pan

Keywords:

Bayesian Network (BN), Cloud Computing, Industrial Cluster, Innovation Assessment

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Padmore T., Gibson H.. Modeling systems of innovation II, a frame work for industrial cluster analysis in regions. Research Policy. 26(6), 625-641. (1998)

Google Scholar

[2] Wei J.. Industry Cluster: Innovation System and Technology Learning. Beijing: Science Press. (2003)

Google Scholar

[3] Wu G. S.. Technology Innovation Management. Beijing: Tsinghua University Press. (2000).

Google Scholar

[4] Liu X. L.. Enterprise Technology Innovation Management. Beijing: Peking University Press. (1997)

Google Scholar

[5] Cai N., Wang J.Y., Liu W.Y.. An Approach to Learning Bayesian Networks from Small Data Set. Journal of Yunnan University (Natural Sciences Edition). 29(4), 359-363, 370. (2007)

Google Scholar

[6] Ding S.B., Ru Y.. Airlines Flight Safety System Assessment Method Based on Bayesian Networks. Journal of Civil Aviation University of China. 27(3), 30-36. (2009)

Google Scholar

[7] Ge J.Z., Wang F., Zhang H.Y.. Simulated Training Score Evaluation Based on Bayesian Networks. Ship Electronic Engineering. 29(8), 133-136, 154. (2009)

Google Scholar

[8] Wang J., Qiu F.F.. The Statistics Index System Construction of Independent Innovation Ability of Enterprises. Journal of Lanzhou Commercial College. 25(2), 105-109. (2009)

Google Scholar