𝔖 Bobbio Scriptorium
✦   LIBER   ✦

A learning algorithm of fuzzy neural networks with triangular fuzzy weights

✍ Scribed by Hisao Ishibuchi; Kitaek Kwon; Hideo Tanaka


Publisher
Elsevier Science
Year
1995
Tongue
English
Weight
733 KB
Volume
71
Category
Article
ISSN
0165-0114

No coin nor oath required. For personal study only.


πŸ“œ SIMILAR VOLUMES


Genetic algorithm-based learning of fuzz
✍ Rafik A. Aliev; Bijan Fazlollahi; Rustam M. Vahidov πŸ“‚ Article πŸ“… 2001 πŸ› Elsevier Science 🌐 English βš– 93 KB

In spite of great importance of fuzzy feed-forward and recurrent neural networks (FNN) for solving wide range of real-world problems, today there is no e ective learning algorithm for FNN. In this paper we propose an e ective geneticbased learning mechanism for FNN with fuzzy inputs, fuzzy weights e

FUNCOM: A constrained learning algorithm
✍ Paris Mastorocostas; John Theocharis πŸ“‚ Article πŸ“… 2000 πŸ› Elsevier Science 🌐 English βš– 384 KB

A novel learning algorithm, the FUNCOM (Fuzzy Neural Constrained Optimization Method) is suggested in this paper, for training fuzzy neural networks. The training task is formulated as a constrained optimization problem, whose objective is twofold: (i) minimization of an error measure, leading to su

Fuzzy neural network with fuzzy signals
✍ Yoichi Hayashi; James J. Buckley; Ernest Czogala πŸ“‚ Article πŸ“… 1993 πŸ› John Wiley and Sons 🌐 English βš– 534 KB

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.

Evolution computation based learning alg
✍ Chunmei He; Youpei Ye πŸ“‚ Article πŸ“… 2011 πŸ› John Wiley and Sons 🌐 English βš– 243 KB

We present two fuzzy conjugate gradient learning algorithms based on evolutionary algorithms for polygonal fuzzy neural networks (PFNN). First, we design a new algorithm, fuzzy conjugate algorithm based on genetic algorithm (GA). In the algorithm, we obtain an optimal learning constant Ξ· by GA and t

Max–min fuzzy Hopfield neural networks a
✍ Puyin Liu πŸ“‚ Article πŸ“… 2000 πŸ› Elsevier Science 🌐 English βš– 117 KB

We set up a dynamical fuzzy neural network system, i.e. the so-called max-min fuzzy HopΓΏeld network in the paper, and prove the Lyapunov stability of the equilibrium points (attractor) of the system. Also, we discuss the uniform stability of the system and show some su cient conditions, with which t