Abstract
Recent advances in networking technology have increased the potential collaborations for virtual enterprises (VEs) on a global scale. Due to the dynamic nature of collaborations, building and evolving trust is essential to support the formation of VEs. There is a critical need for the new approach suited to this environment. This paper presents a trust-based approach for partner selection problem in the VEs. The proposed model explores the dynamic properties of trustworthy index, which provides a multi-perspective and interactive overview of potential partners to the decision-makers. The model uses the hybrid learning algorithm of fuzzy cognitive map (FCM). As FCM has the excellent ability in modeling complex systems, the proposed model can support historical data mining automatically, and revise the existing model according to the new requirements. Results of three experiments show that this model provides reasonable performance and high adaptability for diverse partner selection problems.
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Zhang, W., Zhu, Y. (2007). A Trust-Based Model Using Learning FCM for Partner Selection in the Virtual Enterprises. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues. ICIC 2007. Lecture Notes in Computer Science, vol 4681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74171-8_68
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DOI: https://doi.org/10.1007/978-3-540-74171-8_68
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