Results 261 to 270 of about 190,933 (296)

RULE EXTRACTION WITH FUZZY NEURAL NETWORK

International Journal of Neural Systems, 1994
This paper deals with the learning of understandable decision rules with connectionist systems. Our approach consists of extracting fuzzy control rules with a new fuzzy neural network. Whereas many other works on this area propose to use combinations of nonlinear neurons to approximate fuzzy operations, we use a fuzzy neuron that computes max-min ...
F, D'Alché-Buc, V, Andrès, J P, Nadal
openaire   +2 more sources

Fuzzy Multiresolution Neural Networks

2009
A fuzzy multi-resolution neural network (FMRANN) based on particle swarm algorithm is proposed to approximate arbitrary nonlinear function. The active function of the FMRANN consists of not only the wavelet functions, but also the scaling functions, whose translation parameters and dilation parameters are adjustable.
Li Ying, Shang Qigang, Lei Na
openaire   +1 more source

Fuzzy Chaotic Neural Networks

2009
An understanding of the human brain’s local function has improved in recent years. But the cognition of human brain’s working process as a whole is still obscure. Both fuzzy logic and dynamic chaos are internal features of the human brain. Therefore, to fuse artificial neural networks, fuzzy logic and dynamic chaos together to constitute fuzzy chaotic ...
Tang Mo, Wang Kejun, Zhang Jianmin, Zheng Liying   +3 more
openaire   +1 more source

Fuzzy Logic and Fuzzy Neural Networks

2013
Fuzzy logic provides a method for representing analog processes in a digital framework. Processes that are implemented through fuzzy logic are often not easily separated into discrete segments and may be difficult to model with conventional mathematical or rule-based paradigms that require hard boundaries or decisions, i.e., binary logic where ...
openaire   +1 more source

Fuzzy CMAC Neural Networks

Journal of Intelligent & Fuzzy Systems, 1995
This article reveals the connection between the cerebellar model arithmetic computer (CMAC) neural network and fuzzy inference systems. A novel artificial neural network architecture called the fuzzy CMAC neural network is established that achieves the synergistic combination of the preferred features of the CMAC neural network and the fuzzy logic ...
openaire   +1 more source

Fuzzy Neural Network

2023
Xiu Zhang, Xin Zhang, Wei Wang
openaire   +1 more source

Concurrent Fuzzy Neural Networks

2016
The aim of this chapter is to introduce two concurrent fuzzy neural network approaches for a: (1) Fuzzy Nonlinear Perceptron (FNP) and (2) Fuzzy Gaussian Neural Network (FGNN), each of them representing a winner-takes-all collection of fuzzy modules.
openaire   +1 more source

Reduced Rule-Base Fuzzy-Neural Networks

2017
In this paper two different fuzzy-neural systems with reduced fuzzy rules bases, namely Distributed Adaptive Neuro Fuzzy Architecture (DANFA) and Semi Fuzzy Neural Network (SFNN), are presented. Both structures are realized with Takagi-Sugeno fuzzy inference mechanism and they posses reduced number of parameters for update during the learning procedure.
Terziyska, Margarita, Todorov, Yancho
openaire   +2 more sources

A CONCURRENT FUZZY NEURAL NETWORK APPROACH FOR A FUZZY GAUSSIAN NEURAL NETWORK

Blucher Mechanical Engineering Proceedings, 2014
The aim of the paper is to introduce a concurrent fuzzy neural network approach, representing a winner-takes-all collection of fuzzy Gaussian modules. Our proposed model will be applied for the pattern classification.
openaire   +1 more source

Fuzzy Neural Networks

1999
Evangelia Micheli-Tzanakou, Timothy Dasey   +1 more
openaire   +1 more source