Parameter selection is a well-known problem in the fuzzy clustering community. In this paper, we propose to tackle this problem using a computationally intensive approach. We apply this approach to a new method for clustering recently introduced in the literature. It is the fuzzy c-means with tolera
Fuzzy multicriteria selection of alternatives: The worst-case method
β Scribed by Alexander Rotshtein; Eli Shnaider; Moti Schneider; Abraham Kandel
- Publisher
- John Wiley and Sons
- Year
- 2010
- Tongue
- English
- Weight
- 215 KB
- Volume
- 25
- Category
- Article
- ISSN
- 0884-8173
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β¦ Synopsis
In this article, we propose the method of the multicriteria alternative selection under uncertainty. The basis of the method is the principle of the Bellman-Zadeh fuzzy measures intersection and nine-point linguistic rating scale of Saaty. The novelty of the method presented here consists of the fact that it does not require labor-intensive procedures, requiring arraying and array processing of paired comparisons matrix. Instead, special correlations are used, which are based on the comparison with the worst alternative and the least important criterion. As an example for the utilization of our method, we use the problem for choosing cars.
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