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Fuzzy neural network approach to fuzzy polynomials.

Saeid Abbasbandy, M. Otadi (2006)

Mathware and Soft Computing

In this paper, an architecture of fuzzy neural networks is proposed to find a real root of a dual fuzzy polynomial (if exists) by introducing a learning algorithm. We proposed a learning algorithm from the cost function for adjusting of crisp weights. According to fuzzy arithmetic, dual fuzzy polynomials can not be replaced by a fuzzy polynomials, directly. Finally, we illustrate our approach by numerical examples.

Fuzzy termination criteria in Knapsack Problem algorithms.

José Luis Verdegay, Edmundo Vergara-Moreno (2000)

Mathware and Soft Computing

Fuzzy rule based termination criteria are introduced in two conventional and exact algorithms solving Knapsack Problems. As a consequence two new solution algorithms are obtained. These algorithms are heuristic ones with a high performance. The efficiency of the algorithms obtained is illustrated by solving some numerical examples.

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