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Intelligent Method and Algorithm for Multi-attribute Decision-Making under Linguistic Setting Based on Risk-Weighted

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6 Author(s)

Decision Suppose System is playing an important role in computer science, technology and engineering, while intelligent decision-making is one of the current hotspots. Intelligent decision-making methods and their algorithms are one of the most important basics and key cores in intelligent information processing, intelligent pervasive computing and so on. In view of multi-attribute decision-making under linguistic setting, propose one new decision method. Firstly construct a range pole plan and introduce the policy-maker risk-preference weight because the attributes¿ measure-value are uncertainty. Then with three tuples (Limit low similarity, Risk degree, Risk preference value) reflect the risk-degree existing in the decision-making process. Then construct the risk-weighted similarity measure operator (RWSMO) to measure the risk balance similarity's size between each of decision schemes and the range pole plan.

Published in:

Parallel and Distributed Processing with Applications, 2008. ISPA '08. International Symposium on

Date of Conference:

10-12 Dec. 2008