Optimization of Fuzzy Expert-systems Using Genetic Algorithms and Neural Networks
(1995) IEEE Transactions on Fuzzy Systems — Vol. 3, n° 3, p. 300-312 (1995)
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- Abstract
- In this paper, the fuzzy logic theory is used to build a specific decision-making system for heuristic search algorithms. Such algorithms are typically used for expert systems. To improve the performance of the overall system, a set of important parameters of the decision-making system is identified. Two optimization methods for the learning of the optimum parameters, namely genetic algorithms and gradient-descent techniques based on a neural network formulation of the problem, are used to obtain an improvement of the performance. The decision-making system and both optimization methods are tested on a target recognition system.
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Citations
Perneel, C., Themlin, JM., Renders, JM., & Acheroy, M. (1995). Optimization of Fuzzy Expert-systems Using Genetic Algorithms and Neural Networks. IEEE Transactions on Fuzzy Systems, 3(3), 300-312. https://doi.org/10.1109/91.413235 (Original work published 1995)