Gray Wolf Optimization and Least Square Estimatation As A New Learning Algorithm For Interval Type-II ANFIS

Authors

  • Blqees K. Faraj
  • Nazar K. Hussein

DOI:

https://doi.org/10.25130/tjps.v24i1.339

Abstract

Gray Wolfe Optimization (GWO) is one of the meta-heuristic method and it is a popular technique in Many engineering and economic applications. GWO and Least Square Estimatation (LSE) are used to optimize the antecedents and consequents parameters of interval type-2 ANFIS respectively. We are checking the new learning algorithm by using the interval type-2 ANFIS in prediction of Mackey-Glass time series and the results were very encouraging compared to other algorithms.

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Published

2019-03-18

How to Cite

Blqees K. Faraj, & Nazar K. Hussein. (2019). Gray Wolf Optimization and Least Square Estimatation As A New Learning Algorithm For Interval Type-II ANFIS. Tikrit Journal of Pure Science, 24(1), 107–111. https://doi.org/10.25130/tjps.v24i1.339

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