• DocumentCode
    649825
  • Title

    Interval Type-2 Adaptive Network-based Fuzzy Inference System (ANFIS) with Type-2 non-singleton fuzzification

  • Author

    MonirVaghefi, Hossein ; Rafiee Sandgani, Mohsen ; Aliyari Shoorehdeli, Mahdi

  • Author_Institution
    Dept. of Control Eng., K.N. Toosi Univ. of Technol., Tehran, Iran
  • fYear
    2013
  • fDate
    27-29 Aug. 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this study it is attempted to describe the structure and procedure of training for the Interval Type-2 Fuzzy Logic inference System completely. To achieve this goal Adaptive Network-based Fuzzy Inference System (ANFIS) structure has been generalized to interval type-2 fuzzy, also all of the relations to describe inference structure and all of the necessary differentiation to adjust parameters with Gradient descent and Levenberg-Marquardt method has been brought. Described structure has been used to forecast Mackey-Glass chaotic time-series that polluted with additive uncertain domain noise. Using mentioned procedure for parameters adjustment achieved acceptable results.
  • Keywords
    chaos; fuzzy logic; fuzzy neural nets; fuzzy reasoning; fuzzy set theory; gradient methods; time series; ANFIS structure; Levenberg-Marquardt method; Mackey-Glass chaotic time-series; additive uncertain domain noise; gradient descent method; inference structure; interval type-2 adaptive network-based fuzzy inference system; interval type-2 fuzzy logic inference system; type-2 nonsingleton fuzzification; ANFIS; Fuzzy; Interval Type-2 Fuzzy System; Type-2 non-singleton fuzzifier;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (IFSC), 2013 13th Iranian Conference on
  • Conference_Location
    Qazvin
  • Print_ISBN
    978-1-4799-1227-8
  • Type

    conf

  • DOI
    10.1109/IFSC.2013.6675612
  • Filename
    6675612