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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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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
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Neuro-fuzzy Model-based Control
Journal of Intelligent and Robotic Systems, 1998The paper deals with the Neuro-fuzzy model-based control and its application. Various types of the fuzzy logic and neural-net-based nonlinear autoregressive models with exogenous variables are reviewed with respect to the model error. Two types of model-based neuro-fuzzy control – a cancellation controller and a predictive controller are reviewed – and
Matko, D. +2 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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1998
Neuro-fuzzy classification systems offer means to obtain fuzzy classification rules by a learning algorithm. It is usually possible to find a suitable fuzzy classifier by learning from data, but it can be hard to obtain a classifier that can be interpreted conveniently.
Detlef Nauck +2 more
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Neuro-fuzzy classification systems offer means to obtain fuzzy classification rules by a learning algorithm. It is usually possible to find a suitable fuzzy classifier by learning from data, but it can be hard to obtain a classifier that can be interpreted conveniently.
Detlef Nauck +2 more
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1996
Die in den Kapiteln 17 bis 19 vorgestellten Neuro-Fuzzy-Modelle sind im Hinblick auf einen Einsatz im Bereich der Fuzzy-Regelung entwickelt worden. Damit ist die Anwendbarkeit derartiger Modelle jedoch noch nicht ausgeschopft. Wir haben gesehen, das ein Fuzzy-Regler eine Interpolationsaufgabe lost.
Detlef Nauck +2 more
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Die in den Kapiteln 17 bis 19 vorgestellten Neuro-Fuzzy-Modelle sind im Hinblick auf einen Einsatz im Bereich der Fuzzy-Regelung entwickelt worden. Damit ist die Anwendbarkeit derartiger Modelle jedoch noch nicht ausgeschopft. Wir haben gesehen, das ein Fuzzy-Regler eine Interpolationsaufgabe lost.
Detlef Nauck +2 more
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Proceedings of 19th Convention of Electrical and Electronics Engineers in Israel, 2002
The concept of fuzzy logic has been incorporated into the neural network so as to enable a system to deal with cognitive uncertainties in a manner more like humans. This integration yields the neuro fuzzy system, that captures the benefits of the fuzzy logic as well as the neural network tools into a single approach. Many neuro fuzzy-based applications
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The concept of fuzzy logic has been incorporated into the neural network so as to enable a system to deal with cognitive uncertainties in a manner more like humans. This integration yields the neuro fuzzy system, that captures the benefits of the fuzzy logic as well as the neural network tools into a single approach. Many neuro fuzzy-based applications
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2000
There are generally three approaches to building mathematical models: white box modeling, where everything is considered to be known from physical laws, black box modeling (system identification), where all knowledge derives from measurements, gray box modeling, where both physical laws and observed measurements are used to design a ...
Ernest Czogała, Jacek Łęski
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There are generally three approaches to building mathematical models: white box modeling, where everything is considered to be known from physical laws, black box modeling (system identification), where all knowledge derives from measurements, gray box modeling, where both physical laws and observed measurements are used to design a ...
Ernest Czogała, Jacek Łęski
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Proceedings of IEEE 5th International Fuzzy Systems, 2002
Neural VLSI devices are now available and it would be interesting to use them for logical operations. We show that, in the Lukasiewicz logic, it is possible to use an artificial neuron to implement four basic logical operators (conjunction, disjunction, implication and negation). A new operator, AND-OR, is introduced with the same formalism. Finally, a
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Neural VLSI devices are now available and it would be interesting to use them for logical operations. We show that, in the Lukasiewicz logic, it is possible to use an artificial neuron to implement four basic logical operators (conjunction, disjunction, implication and negation). A new operator, AND-OR, is introduced with the same formalism. Finally, a
openaire +1 more source