In this paper we show how a neural net can be used to solve A3~ C', for X, even though for some values of A and there is no fuzzy arithmetic solution for X. The neural net solution is identified with our new solution [6] to fuzzy equations.
Solving fuzzy equations using evolutionary algorithms and neural nets
โ Scribed by J. J. Buckley; T. Feuring; Y. Hayashi
- Book ID
- 106169782
- Publisher
- Springer
- Year
- 2002
- Tongue
- English
- Weight
- 142 KB
- Volume
- 6
- Category
- Article
- ISSN
- 1432-7643
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๐ SIMILAR VOLUMES
In this paper, we first design a fuzzy neuron which possesses some generality. This fuzzy neuron is founded by replacing the operators of the traditional neuron with a pair of abstract fuzzy operators as (~, ~ ) which we call fuzzy neuron operators. For example, it may be (+, o), (A, "), (V, o), or
In our previous work (Li and Ruan, 1997) we proposed a max-min operator network and a series of training algorithms, called fuzzy rules, which could be used to solve fuzzy relation equations. The most basic and important result is the convergence theorem of fuzzy perceptron based on max-min operator