Automatic Manufacturing Cloud Service Composition Based on AI Plan

Pei Si Zhong; Shao Qi Zhu; De Jie Huang; Hai Liang Xin

doi:10.4028/www.scientific.net/AMM.513-517.990

Paper Titles

Game Optimization for RSA Signature Scheme
p.969

A Heuristic Attribute Reduction Based on Multi-Granularity Rough Set
p.973

An Improved KNN Classification Method Based on Variable Precision Rough Set
p.978

The Research of the Web Service Test Model
p.983

Automatic Manufacturing Cloud Service Composition Based on AI Plan
p.990

Research of Multiple Constrained Qos Routing Based on Improved Ant Colony Algorithm
p.994

Multiple-Replica Public Auditing Protocol for Cloud Storage
p.999

An Improved Watermarking-Based Algorithm of Tamper Detection for Low-Cost EPC C1G2 RFID Tags
p.1005

Development of Virtual Prototype Template File Generator
p.1009

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 513-517Automatic Manufacturing Cloud Service Composition...

Automatic Manufacturing Cloud Service Composition Based on AI Plan

Abstract:

Manufacturing cloud service composition is the key way to improve the utilization of manufacturing resources and manufacturing capabilities, realize added value and efficiency of manufacturing resources and manufacturing capabilities. It has great significance on cloud manufacturing implementation and carry. Therefore, the paper presents automatic forwarding search method called AMCSC-HFS for manufacturing cloud service composition based on AI plan. The main purpose is to support meeting the actual need of large-scale and dynamic cloud manufacturing cloud service environment.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 513-517)

Pages:

990-993

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.513-517.990

Citation:

Cite this paper

Online since:

February 2014

Authors:

Pei Si Zhong*, Shao Qi Zhu, De Jie Huang, Hai Liang Xin

Keywords:

AMCSC-HFS, Automatic Composition, Forwarding Search, Manufacturing Cloud Service

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] T. Bylander. Complexity Results for Planning[C]. Proceedings of the Twelfth International Joint Conference on Artificial Intelligence, (1991).

Google Scholar

[2] A. Blum, M. Furst. Fast Planning through Planning Graph Analysis[J]. Journal of Artificial Intelligence, 1997, 90: 281-300.

DOI: 10.1016/s0004-3702(96)00047-1

Google Scholar

[3] J. Hoffmam, B. Nebel. The FF Planning System: Fast Plan Generation through Heuristic Search [J]. Journal of Artificial Intelligence Research, 2001, 14: 253-302.

DOI: 10.1613/jair.855

Google Scholar

[4] SeogChan, ByungWon, LarsonEric, et al. BF*: Web Services Discovery and Composition as Graph Search Problem[C]. Proceedings of the 2005 IEEE International Conference on E-Technology, E-Commerce and E-Service, HongKong, 2005: 784-786.

DOI: 10.1109/eee.2005.41

Google Scholar

[5] Tao fei, Zhang lin, Guo hua, etal. Typical characteristics of cloud manufacturing and several key issues of cloud service composition [J]. Computer Integrated Manufacturing Systems, 2011, 17(3): 477-48.

Google Scholar