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HyFIS: adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems

Authors:

J. Kim,

N. KasabovAuthors Info & Claims

Neural Networks, Volume 12, Issue 9

Pages 1301 - 1319

https://doi.org/10.1016/S0893-6080(99)00067-2

Published: 01 November 1999 Publication History

Abstract

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Kumar AArora HKumar KGarg H(2023)Performance prognosis of FRCM-to-concrete bond strength using ANFIS-based fuzzy algorithmExpert Systems with Applications: An International Journal10.1016/j.eswa.2022.119497216:COnline publication date: 15-Apr-2023
https://dl.acm.org/doi/10.1016/j.eswa.2022.119497
Ouifak HIdri A(2023)Application of neuro-fuzzy ensembles across domainsEngineering Applications of Artificial Intelligence10.1016/j.engappai.2023.106582124:COnline publication date: 1-Sep-2023
https://dl.acm.org/doi/10.1016/j.engappai.2023.106582
Bhagat STiyasha TAl-khafaji ZLaux PEwees ARashid TSalih SYonaba RBeyaztas UYaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬ Z(2022)Establishment of Dynamic Evolving Neural-Fuzzy Inference System Model for Natural Air Temperature PredictionComplexity10.1155/2022/10473092022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/1047309
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Index Terms

HyFIS: adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
      1. Probabilistic reasoning
      2. Vagueness and fuzzy logic
  2. Machine learning
    1. Learning settings
    2. Machine learning approaches
      1. Neural networks
2. Mathematics of computing

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Information

Published In

Neural Networks Volume 12, Issue 9

Nov. 1999

119 pages

ISSN:0893-6080

Editors:
Stephen Grossberg
Boston Univ., Boston, MA
,
Mitsuo Kawato
ATR Research Lab, Kyoto, Japan
,
John Taylor
Univ. of London, Strand, London

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Elsevier Science Ltd.

United Kingdom

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Published: 01 November 1999

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Kumar AArora HKumar KGarg H(2023)Performance prognosis of FRCM-to-concrete bond strength using ANFIS-based fuzzy algorithmExpert Systems with Applications: An International Journal10.1016/j.eswa.2022.119497216:COnline publication date: 15-Apr-2023
https://dl.acm.org/doi/10.1016/j.eswa.2022.119497
Ouifak HIdri A(2023)Application of neuro-fuzzy ensembles across domainsEngineering Applications of Artificial Intelligence10.1016/j.engappai.2023.106582124:COnline publication date: 1-Sep-2023
https://dl.acm.org/doi/10.1016/j.engappai.2023.106582
Bhagat STiyasha TAl-khafaji ZLaux PEwees ARashid TSalih SYonaba RBeyaztas UYaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬ Z(2022)Establishment of Dynamic Evolving Neural-Fuzzy Inference System Model for Natural Air Temperature PredictionComplexity10.1155/2022/10473092022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/1047309
Li LLong ZYing HQiao Z(2022)An online gradient-based parameter identification algorithm for the neuro-fuzzy systemsFuzzy Sets and Systems10.1016/j.fss.2020.11.003426:C(27-45)Online publication date: 15-Jan-2022
https://dl.acm.org/doi/10.1016/j.fss.2020.11.003
Navarro-Almanza RSanchez MCastro JMendoza OLicea G(2022)Interpretable Mamdani neuro-fuzzy model through context awareness and linguistic adaptationExpert Systems with Applications: An International Journal10.1016/j.eswa.2021.116098189:COnline publication date: 1-Mar-2022
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Verma BPrasad RSrivastava PYadav SSingh PSingh R(2022)Investigation of optimal vegetation indices for retrieval of leaf chlorophyll and leaf area index using enhanced learning algorithmsComputers and Electronics in Agriculture10.1016/j.compag.2021.106581192:COnline publication date: 1-Jan-2022
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Averkin AYarushev S(2021)Review of Research in the Field of Developing Methods to Extract Rules From Artificial Neural NetworksJournal of Computer and Systems Sciences International10.1134/S106423072106004660:6(966-980)Online publication date: 1-Nov-2021
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Nguyen HBui XBui HMai N(2020)A comparative study of artificial neural networks in predicting blast-induced air-blast overpressure at Deo Nai open-pit coal mine, VietnamNeural Computing and Applications10.1007/s00521-018-3717-532:8(3939-3955)Online publication date: 1-Apr-2020
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Pinto TMorais HCorchado J(2019)Adaptive entropy-based learning with dynamic artificial neural networkNeurocomputing10.1016/j.neucom.2018.09.092338:C(432-440)Online publication date: 21-Apr-2019
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Dang KBurkhard BWindhorst WMüller F(2019)Application of a hybrid neural-fuzzy inference system for mapping crop suitability areas and predicting rice yieldsEnvironmental Modelling & Software10.1016/j.envsoft.2019.01.015114:C(166-180)Online publication date: 1-Apr-2019
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