Results 151 to 160 of about 63,417 (204)
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1998
This paper is about so-called 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 definition, and still has the flavour of a buzzword to it.
Rudolf Kruse, Detlef Nauck
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This paper is about so-called 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 definition, and still has the flavour of a buzzword to it.
Rudolf Kruse, Detlef Nauck
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Neuro-Fuzzy Systems and their Applications
2008 7th Computer Information Systems and Industrial Management Applications, 2008Summary form only given. In the lecture, we incorporate various flexibility parameters to the construction of neuro-fuzzy systems. This approach dramatically improves their performance, allowing the systems to perfectly represent the pattern encoded in data.
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2018
A hybrid intelligent system involves combining two intelligent technologies; e.g., a combination of a neural network with a fuzzy system to produce a hybrid neuro-fuzzy system. Generally combining probabilistic reasoning, fuzzy logic, evolutionary computation together with neural networks produces hybrid systems which form the core of soft computing.
Alireza Hajian, Peter Styles
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A hybrid intelligent system involves combining two intelligent technologies; e.g., a combination of a neural network with a fuzzy system to produce a hybrid neuro-fuzzy system. Generally combining probabilistic reasoning, fuzzy logic, evolutionary computation together with neural networks produces hybrid systems which form the core of soft computing.
Alireza Hajian, Peter Styles
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Superior neuro-fuzzy classification systems
Neural Computing and Applications, 2012Although adaptive neuro-fuzzy inference system (ANFIS) has very fast convergence time, it is not suitable for classification problems because its outputs are not integer. In order to overcome this problem, this paper provides four adaptive neuro-fuzzy classifiers; adaptive neuro-fuzzy classifier with linguistic hedges (ANFCLH), linguistic hedges neuro ...
Ahmad Taher Azar, Shaimaa Ahmed El-Said
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2001
This Chapter deals with neuro-fuzzy systems, i. e., those soft computing methods that combine in various ways neural networks and fuzzy concepts. Each methodology has its particular strengths and weaknesses that make it more or less suitable in a given context.
Andrea Tettamanzi, Marco Tomassini
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This Chapter deals with neuro-fuzzy systems, i. e., those soft computing methods that combine in various ways neural networks and fuzzy concepts. Each methodology has its particular strengths and weaknesses that make it more or less suitable in a given context.
Andrea Tettamanzi, Marco Tomassini
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Neuro Fuzzy Modeling of Control Systems
16th International Conference on Electronics, Communications and Computers (CONIELECOMP'06), 2006The analysis of the models is carried out starting from experimental data of a multivariable system MISO (Many Input Single Output). The models implementation was made using fuzzy logic. In fuzzy logic, the cluster technique was used to decrease the number of rules to use in the identification.
Efrén Gorrostieta Hurtado +1 more
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2017
Die in Kap. 8 behandelte Neuro-Fuzzy-Technologie vereint die Vorteile der Fuzzy-Logik mit ihren Moglichkeiten, unscharfe Mengen mathematisch zu behandeln, mit denen kunstlicher neuronaler Netze, deren Wissen in den Eigenschaften und der Vernetzung der einzelnen Neuronen gespeichert ist.
Zbigniew A. Styczynski +2 more
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Die in Kap. 8 behandelte Neuro-Fuzzy-Technologie vereint die Vorteile der Fuzzy-Logik mit ihren Moglichkeiten, unscharfe Mengen mathematisch zu behandeln, mit denen kunstlicher neuronaler Netze, deren Wissen in den Eigenschaften und der Vernetzung der einzelnen Neuronen gespeichert ist.
Zbigniew A. Styczynski +2 more
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A neuro-fuzzy systems for control applications
1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report, 2002This paper describes DANIELA a neuro-fuzzy system for control applications. The system is based on a custom neural device that can implement either multilayer perceptrons, radial basis functions or fuzzy paradigms. The system implements intelligent control algorithms mixing neuro-fuzzy paradigms with finite state automata and is used to control a ...
F. BERARDI +3 more
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1993
Bei der Erstellung von Fuzzy Systemen ist ein auf Expertenwissen basierender oder heuristischer Ansatz zur Modellierung der zugehorigen Steuerregeln notwendig. Zur Erstellung von Adaptiven Fuzzy Systemen bietet der Einsatz von Neuronalen Netzwerken eine methodische Alternative zum Entwurf und zur Optimierung der Fuzzy-SystemParameter.
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Bei der Erstellung von Fuzzy Systemen ist ein auf Expertenwissen basierender oder heuristischer Ansatz zur Modellierung der zugehorigen Steuerregeln notwendig. Zur Erstellung von Adaptiven Fuzzy Systemen bietet der Einsatz von Neuronalen Netzwerken eine methodische Alternative zum Entwurf und zur Optimierung der Fuzzy-SystemParameter.
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Neuro-fuzzy systems for function approximation
Fuzzy Sets and Systems, 1999The idea of exploiting learning capabilities of neural networks in order to automate or support the process of developing a fuzzy system for a given task has been developed for a long time. The authors of the reviewed paper themselves used neuro-fuzzy systems already in the domain of (neuro-) fuzzy control, data analysis and classification.
Detlef D. Nauck, Rudolf Kruse
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