Fuzzy neural network with fuzzy signals and weights
β Scribed by Yoichi Hayashi; James J. Buckley; Ernest Czogala
- Publisher
- John Wiley and Sons
- Year
- 1993
- Tongue
- English
- Weight
- 534 KB
- Volume
- 8
- Category
- Article
- ISSN
- 0884-8173
No coin nor oath required. For personal study only.
β¦ Synopsis
We discuss the direct fuzzification of a standard layered, feedforward, neural network where the signals and weights are fuzzy sets. A fuzzified delta rule is presented for learning. Three applications are given including fuzzy expert systems, fuzzy hierarchical analysis, and fuzzy systems modeling.
π SIMILAR VOLUMES
In this paper, we describe a method for nonlinear fuzzy regression using neural network models. In earlier work, strong assumptions were made on the form of the fuzzy number parameters: symmetric triangular, asymmetric triangular, quadratic, trapezoidal, and so on. Our goal here is to substantially
This paper presents a practical algorithm for training neural networks with fuzzy number weights, inputs, and outputs. Typically, fuzzy number neural networks are di cult to train because of the many -cut constraints implied by the fuzzy weights. A transformation is used to eliminate these constrain