𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Fuzzy Neural Network Models for Classification

✍ Scribed by Arun D. Kulkarni; Charles D. Cavanaugh


Book ID
110262998
Publisher
Springer US
Year
2000
Tongue
English
Weight
302 KB
Volume
12
Category
Article
ISSN
0924-669X

No coin nor oath required. For personal study only.


πŸ“œ SIMILAR VOLUMES


Fuzzy neural network models for liquefac
✍ M.S Rahman; Jun Wang πŸ“‚ Article πŸ“… 2002 πŸ› Elsevier Science 🌐 English βš– 243 KB

Integrated fuzzy neural network models are developed for the assessment of liquefaction potential of a site. The models are trained with large databases of liquefaction case histories. A two-stage training algorithm is used to develop a fuzzy neural network model. In the preliminary training stage,

A fuzzy neural network algorithm for mul
✍ Ralf Γ–stermark πŸ“‚ Article πŸ“… 1999 πŸ› Elsevier Science 🌐 English βš– 692 KB

We propose a multigroup classification algorithm based on a hybrid fuzzy neural net framework. A key feature of the approach is the adaptation of membership functions to new data. In this way, learning is reflected in the shape of the membership functions. By defining separate membership functions f

Evaluation of fuzzy regression models by
✍ M. Mosleh; M. Otadi; S. Abbasbandy πŸ“‚ Article πŸ“… 2010 πŸ› Elsevier Science 🌐 English βš– 378 KB

## a b s t r a c t In this paper, a novel hybrid method based on fuzzy neural network for approximate fuzzy coefficients (parameters) of fuzzy linear and nonlinear regression models with fuzzy output and crisp inputs, is presented. Here a neural network is considered as a part of a large field call