نتایج جستجو برای: fuzzy neural net

تعداد نتایج: 477041  

2001
Ajith Abraham

Fuzzy inference systems and neural networks are complementary technologies in the design of adaptive intelligent systems. Artificial Neural Network (ANN) learns from scratch by adjusting the interconnections between layers. Fuzzy Inference System (FIS) is a popular computing framework based on the concept of fuzzy set theory, fuzzy if-then rules, and fuzzy reasoning. A neuro-fuzzy system is sim...

Journal: :journal of medical signals and sensors 0
zahra vahabi saeed kermani

unknown noise and artifacts present in medical signals with  non-linear fuzzy filter will be estimate and then removed. an adaptive neuro-fuzzy interference system which has a nonlinear  structure presented  for the noise function prediction by before samples. this paper is about a neuro-fuzzy method to estimate unknown noise of electrocardiogram (ecg) signal. adaptive neural combined with fuzz...

1997
Detlef Nauck

This paper reviews neuro-fuzzy systems, which combine methods from neural network theory with fuzzy systems. Such combinations have been considered for several years already. However, the term neuro-fuzzy still lacks proper deenition, and still has the avour of a buzzword to it. Surprisingly few neuro-fuzzy approaches do actually employ neural networks, even though they are very often depicted ...

fereidouni, Sepide , moradian borojeni , Pegah , Zare Mehrjerdi , Yahia ,

With the existence of ambiguity in the financial processes of projects, fuzzy concepts are being implemented into the foundation and essence of the current article. Authors have employed chance constrained programming and simulated annealing as appropriate tools for determining the net present worth value of several projects. At the end, the most economical project was chosen. In this article, ...

2009
LUCIEN NGALAMOU

This paper presents a design approach intended for the modeling and synthesis of discrete-event modules of hybrid controllers by combining a model of computation and a soft computing synthesis approach. The model of computation is based on coloured Petri nets (CPNs) and the soft computing method uses fuzzy logic. The design approach converts Petri net models into their equivalent fuzzy sets for...

2011
Lyes Saad Saoud Fayçal Rahmoune Victor Tourtchine Kamel Baddari

In this paper, a new architecture combining dynamic neural units and fuzzy logic approaches is proposed for a complex chemical process modeling. Such processes need a particular care where the designer constructs the neural network, the fuzzy and the fuzzy neural network models which are very useful in black box modeling. The proposed architecture is specified to the pH chemical reactor due to ...

Journal: :amirkabir international journal of modeling, identification, simulation & control 2014
a. fakharian r. mosaferin m. b. menhaj

in this paper, a recurrent fuzzy-neural network (rfnn) controller with neural network identifier in direct control model is designed to control the speed and exhaust temperature of the gas turbine in a combined cycle power plant. since the turbine operation in combined cycle unit is considered, speed and exhaust temperature of the gas turbine should be simultaneously controlled by fuel command ...

Journal: :CoRR 2010
Yasser M. Alginaih Abdul Ahad Siddiqi

The use of OCR in postal services is not yet universal and there are still many countries that process mail sorting manually. Automated Arabic/Indian numeral Optical Character Recognition (OCR) systems for Postal services are being used in some countries, but still there are errors during the mail sorting process, thus causing a reduction in efficiency. The need to investigate fast and efficien...

1995
Hugues Bersini Gianluca Bontempi Christine Decaestecker

This paper aims at helping to clarify the current confusion raised by a lot of workscomparing or merging neural net with fuzzy inference systems. On the theoretical side,we first show that a specific family of neural nets: Radial-Basis Functions (RBF) and aspecific family of fuzzy inference systems: Tagaki-Sugeno fuzzy inference systems (FIS)are nearly equivalent structure altho...

Journal: :Fuzzy Sets and Systems 2005
Shinq-Jen Wu Hsin-Han Chiang Han-Tsung Lin Tsu-Tian Lee

Aneural-learning fuzzy technique is proposed for T–S fuzzy-model identification ofmodel-free physical systems. Further, an algorithm with a defined modelling index is proposed to integrate and to guarantee that the proposed neural-based optimal fuzzy controller can stabilize physical systems; the modelling index is defined to denote the modelling-error evolution, and to ensure that the training...

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