Results 191 to 200 of about 53,858 (257)
Transformer hot spot temperature estimation through adaptive neuro fuzzy inference system approach. [PDF]
HeliyonMharakurwa ET, Gicheru DW.
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Adaptive neuro-fuzzy inference system for forecasting corrosion rates of automotive parts in biodiesel environment. [PDF]
HeliyonSamuel OD +4 more
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International Journal of Neural Systems, 2006
Fuzzy decision trees are powerful, top-down, hierarchical search methodology to extract human interpretable classification rules. However, they are often criticized to result in poor learning accuracy. In this paper, we propose Neuro-Fuzzy Decision Trees (N-FDTs); a fuzzy decision tree structure with neural like parameter adaptation strategy.
Rajen B. Bhatt, M. Gopal
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Fuzzy decision trees are powerful, top-down, hierarchical search methodology to extract human interpretable classification rules. However, they are often criticized to result in poor learning accuracy. In this paper, we propose Neuro-Fuzzy Decision Trees (N-FDTs); a fuzzy decision tree structure with neural like parameter adaptation strategy.
Rajen B. Bhatt, M. Gopal
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A neuro-fuzzy framework for inferencing
Neural Networks, 2002Earlier we proposed a connectionist implementation of compositional rule of inference (COI) for rules with antecedents having a single clause. We first review this net, then generalize it so that it can deal with rules with antecedent having multiple clauses. We call it COIN, the compositional rule of inferencing network.
Sukumar Chakraborty +2 more
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Neuro-fuzzy systems for diagnosis
Fuzzy Sets and Systems, 1997Abstract Knowledge-based fault detection and diagnosis is described from the analytic and heuristic symptom generation to diagnostic reasoning. The extension of the knowledge-based approach by adaptive neural networks allows us to tune the knowledge base in order to investigate undetermined parameters just as membership functions, relevance weights ...
Mihiar Ayoubi, Rolf Isermann
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Simplifying a neuro-fuzzy model
Neural Processing Letters, 1996Neuro-fuzzy modeling allows a fuzzy system to be refined by neural training, thus avoiding lenghty trial-and-error phases in defining both membership functions and inference rules. An approach to obtain simple neuro-fuzzy models is proposed, which reduces the number of rules by means of a systematic procedure that consists in successively removing a ...
Giovanna Castellano, Anna Maria Fanelli
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Intelligent Automation & Soft Computing, 1999
ABSTRACTIn this paper, a new analog neuro-fuzzy controller is presented. Standard CMOS technology was used for implementation of the building blocks. Internal architecture provides the trade-off between speed and the number of fuzzy rules and/or number of antecedents. Although the input signals, output signals and the processor circuits are all analog,
Nasser Sadati, Hooman Mohseni
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ABSTRACTIn this paper, a new analog neuro-fuzzy controller is presented. Standard CMOS technology was used for implementation of the building blocks. Internal architecture provides the trade-off between speed and the number of fuzzy rules and/or number of antecedents. Although the input signals, output signals and the processor circuits are all analog,
Nasser Sadati, Hooman Mohseni
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Neuro-Fuzzy Identifiers and Controllers
Journal of Intelligent & Fuzzy Systems, 1994A neuro-fuzzy identifier for fuzzy modeling of a system is explained, and a control structure using this neurofuzzy identifier is proposed. The neuro-fuzzy identifier contains not only an adaptive clustering process for determining center points of the input and virtual output membership functions but also an adaptive process for deciding the shapes of
M.Lee +2 more
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IEEE Transactions on Cybernetics, 2013
In this paper, a novel neuro-fuzzy computing system is proposed where its learning is based on the creation of fuzzy relations by using a new implication method without utilizing any exact mathematical techniques. Then, a simple memristor crossbar-based analog circuit is designed to implement this neuro-fuzzy system which offers very interesting ...
Farnood Merrikh-Bayat +1 more
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In this paper, a novel neuro-fuzzy computing system is proposed where its learning is based on the creation of fuzzy relations by using a new implication method without utilizing any exact mathematical techniques. Then, a simple memristor crossbar-based analog circuit is designed to implement this neuro-fuzzy system which offers very interesting ...
Farnood Merrikh-Bayat +1 more
openaire +2 more sources