• DocumentCode
    3725315
  • Title

    Extreme Learning ANFIS for classification problems

  • Author

    Abhinav Tushar; Abhinav;G. N. Pillai

  • Author_Institution
    Department of Electrical Engineering, Indian Institute of Technology, Roorkee, India
  • fYear
    2015
  • Firstpage
    784
  • Lastpage
    787
  • Abstract
    This paper compares Extreme Learning ANFIS (ELANFIS) with conventional ANFIS for classification problems. ELANFIS is a hybrid Fuzzy System based on Extreme Learning Machines. It combines the linguistic knowledge representation of a Fuzzy System with the fast learning speed of ELMs. This paper also proposes the use of a zero order ELANFIS for classification tasks and compares it with first order Fuzzy Systems. The results show that zero order ELANFIS gives lesser classification error with faster learning speed as compared to the mentioned methods since the number of parameters to tune is lesser.
  • Keywords
    "Training","Fuzzy systems","Fuzzy logic","Yttrium","Mathematical model","Input variables","Next generation networking"
  • Publisher
    ieee
  • Conference_Titel
    Next Generation Computing Technologies (NGCT), 2015 1st International Conference on
  • Type

    conf

  • DOI
    10.1109/NGCT.2015.7375227
  • Filename
    7375227