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Fuzzy synthetic rating and a satisfying solution for Lee–Tanaka’s LP problem

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Abstract

Fuzzy synthetic rating is a mapping to capture the relationship between the characteristics of an object in a group and its overall fuzzy rating. This paper presents a general treatment on the problems of fuzzy synthetic rating based on factor space, fuzzy clustering and Lee–Tanaka’s idea of transferring the learning task of fuzzy regression NN by means of solving a kind of linear programming, called Lee–Tanaka’s LP problem by the author here. The author presents a satisfying solution for the LP problem. The satisfying solution is not necessarily an optimal solution in the traditional sense. That is, the fuzzy optimal methodology could be applied even when the feasible region is empty.

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Authors and Affiliations

  1. Department of Engineering and Computer Science, West Texas A&M University, Canyon, TX, 79016, USA

    R. Alex

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  1. R. Alex
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Correspondence to R. Alex.

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Alex, R. Fuzzy synthetic rating and a satisfying solution for Lee–Tanaka’s LP problem. Soft Comput 11, 901–910 (2007). https://doi.org/10.1007/s00500-006-0141-z

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  • DOI: https://doi.org/10.1007/s00500-006-0141-z

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