DocumentCode :
2605493
Title :
Trust evaluation of CoPS partners based on wavelet support vector machine model and its application
Author :
Long-ying, Hu ; Zhi-sheng, Wang ; Hui-ying, Li ; Xiang-rong, Zhang
Author_Institution :
Sch. of Manage., Harbin Inst. of Technol., Harbin, China
fYear :
2010
fDate :
24-26 Nov. 2010
Firstpage :
1456
Lastpage :
1463
Abstract :
The integrators are facing the problems of so many decision attributes and few data samples for decision-making analysis when evaluating the partners of collaboration and innovation in complex products and systems(CoPS). Firstly, this paper created a trust evaluation model of collaborative partners in CoPS. Secondly, followed by the application of RS attribute reduction as a data pre-processing removes the redundancy in the decision-making property, and then combined with support vector machines (SVM) and wavelet function, this paper established wavelet support vector machines (WSVM) model, then used this model to accomplish the trust evaluation and classification of partners of collaboration and innovation. Compared with the traditional SVM, WSVM model can deal with the time series data, improve the classification performance, and reduce data dimensionality and the complexity classification of in the process, which helps decision-makers to achieve the confidence of partners in collaborative innovation evaluation and chosen. Finally, the method has been applied to the trust assessment process of CoPS System Integrators to core suppliers, and then paper elaborated the actual operation of the method steps and preliminary finished verification about the validity of the model.
Keywords :
decision making; production engineering computing; security of data; support vector machines; wavelet transforms; CoPS partners; CoPS system integrators; RS attribute reduction; collaborative innovation evaluation; complex products; complex systems; data pre-processing; decision attributes; decision-making analysis; trust assessment process; trust evaluation model; wavelet function; wavelet support vector machine model; Collaboration; Decision making; Indexes; Kernel; Support vector machines; Technological innovation; Training; complex products and systems; partner selection; rough set theory; support vector machine; trust evaluation; wavelet functions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Management Science and Engineering (ICMSE), 2010 International Conference on
Conference_Location :
Melbourne, VIC
ISSN :
2155-1847
Print_ISBN :
978-1-4244-8116-3
Type :
conf
DOI :
10.1109/ICMSE.2010.5719979
Filename :
5719979
Link To Document :
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