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- Neuro-fuzzy abstract "In the field of artificial intelligence, neuro-fuzzy refers to combinations of artificial neural networks and fuzzy logic. Neuro-fuzzy was proposed by J. S. R. Jang. Neuro-fuzzy hybridization results in a hybrid intelligent system that synergizes these two techniques by combining the human-like reasoning style of fuzzy systems with the learning and connectionist structure of neural networks. Neuro-fuzzy hybridization is widely termed as Fuzzy Neural Network (FNN) or Neuro-Fuzzy System (NFS) in the literature. Neuro-fuzzy system (the more popular term is used henceforth) incorporates the human-like reasoning style of fuzzy systems through the use of fuzzy sets and a linguistic model consisting of a set of IF-THEN fuzzy rules. The main strength of neuro-fuzzy systems is that they are universal approximators with the ability to solicit interpretable IF-THEN rules.The strength of neuro-fuzzy systems involves two contradictory requirements in fuzzy modeling: interpretability versus accuracy. In practice, one of the two properties prevails. The neuro-fuzzy in fuzzy modeling research field is divided into two areas: linguistic fuzzy modeling that is focused on interpretability, mainly the Mamdani model; and precise fuzzy modeling that is focused on accuracy, mainly the Takagi-Sugeno-Kang (TSK) model.Although generally assumed to be the realization of a fuzzy system through connectionist networks, this term is also used to describe some other configurations including:Deriving fuzzy rules from trained RBF networks.Fuzzy logic based tuning of neural network training parameters.Fuzzy logic criteria for increasing a network size.Realising fuzzy membership function through clustering algorithms in unsupervised learning in SOMs and neural networks.Representing fuzzification, fuzzy inference and defuzzification through multi-layers feed-forward connectionist networks.It must be pointed out that interpretability of the Mamdani-type neuro-fuzzy systems can be lost. To improve the interpretability of neuro-fuzzy systems, certain measures must be taken, wherein important aspects of interpretability of neuro-fuzzy systems are also discussed.A recent research line addresses the data stream mining case, where neuro-fuzzy systems are sequentially updated with new incoming samples on demand and on-the-fly. Thereby, system updates do not only include a recursive adaptation of model parameters, but also a dynamic evolution and pruning of model components (neurons, rules), in order to handle concept drift and dynamically changing system behavior adequately and to keep the systems/models \"up-to-date\" anytime. Comprehensive surveys of various evolving neuro-fuzzy systems approaches can be found in and.".
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- Neuro-fuzzy wikiPageRevisionID "621455568".
- Neuro-fuzzy wikiPageWikiLink Algorithm.
- Neuro-fuzzy wikiPageWikiLink Artificial_intelligence.
- Neuro-fuzzy wikiPageWikiLink Artificial_neural_network.
- Neuro-fuzzy wikiPageWikiLink Category:Artificial_intelligence.
- Neuro-fuzzy wikiPageWikiLink Cluster_analysis.
- Neuro-fuzzy wikiPageWikiLink Concept_drift.
- Neuro-fuzzy wikiPageWikiLink Connectionism.
- Neuro-fuzzy wikiPageWikiLink Data_stream_mining.
- Neuro-fuzzy wikiPageWikiLink Defuzzification.
- Neuro-fuzzy wikiPageWikiLink Fuzzy_control_system.
- Neuro-fuzzy wikiPageWikiLink Fuzzy_logic.
- Neuro-fuzzy wikiPageWikiLink Fuzzy_rule.
- Neuro-fuzzy wikiPageWikiLink Fuzzy_set.
- Neuro-fuzzy wikiPageWikiLink Hybrid_intelligent_system.
- Neuro-fuzzy wikiPageWikiLink Indicator_function.
- Neuro-fuzzy wikiPageWikiLink J._S._R._Jang.
- Neuro-fuzzy wikiPageWikiLink Mamdani_model.
- Neuro-fuzzy wikiPageWikiLink Popular_psychology.
- Neuro-fuzzy wikiPageWikiLink Radial_basis_function.
- Neuro-fuzzy wikiPageWikiLink Self-organizing_map.
- Neuro-fuzzy wikiPageWikiLink Takagi-Sugeno-Kang_(TSK)_model.
- Neuro-fuzzy wikiPageWikiLink Universal_approximation_theorem.
- Neuro-fuzzy wikiPageWikiLink Unsupervised_learning.
- Neuro-fuzzy wikiPageWikiLinkText "Neuro-fuzzy".
- Neuro-fuzzy wikiPageWikiLinkText "neuro-fuzzy system".
- Neuro-fuzzy wikiPageWikiLinkText "neuro-fuzzy".
- Neuro-fuzzy wikiPageUsesTemplate Template:Cleanup-rewrite.
- Neuro-fuzzy subject Category:Artificial_intelligence.
- Neuro-fuzzy type Area.
- Neuro-fuzzy type Area.
- Neuro-fuzzy comment "In the field of artificial intelligence, neuro-fuzzy refers to combinations of artificial neural networks and fuzzy logic. Neuro-fuzzy was proposed by J. S. R. Jang. Neuro-fuzzy hybridization results in a hybrid intelligent system that synergizes these two techniques by combining the human-like reasoning style of fuzzy systems with the learning and connectionist structure of neural networks.".
- Neuro-fuzzy label "Neuro-fuzzy".
- Neuro-fuzzy sameAs Q4165150.
- Neuro-fuzzy sameAs نظام_عصبي_ضبابي.
- Neuro-fuzzy sameAs m.07zn7s.
- Neuro-fuzzy sameAs Нейро-нечеткие_системы.
- Neuro-fuzzy sameAs Neuro-fuzzy.
- Neuro-fuzzy sameAs Q4165150.
- Neuro-fuzzy wasDerivedFrom Neuro-fuzzy?oldid=621455568.
- Neuro-fuzzy isPrimaryTopicOf Neuro-fuzzy.