Fuzzy Wavelet Neural Network Learning Using Artificial Bee Colony Algorithm

Publish Year: 1391
نوع سند: مقاله کنفرانسی
زبان: English
View: 1,620

This Paper With 6 Page And PDF Format Ready To Download

  • Certificate
  • من نویسنده این مقاله هستم

این Paper در بخشهای موضوعی زیر دسته بندی شده است:

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این Paper:

شناسه ملی سند علمی:

ICEE20_163

تاریخ نمایه سازی: 14 مرداد 1391

Abstract:

This paper presents a new hybrid algorithm for Fuzzy Wavelet Neural Network (FWNN) design. Proposed algorithm uses Orthogonal Least Square (OLS) algorithm to purifycandidate wavelets and Artificial Bee Colony (ABC) Algorithm to learn FWNN. In the proposed network, the fuzzy rulecorresponds to one sub-wavelet neural network (sub-WNN) which corresponds to wavelets with a specified dilation value. Orthogonal least square algorithm is used to choose efficientwavelets and to determine the number of fuzzy rules for network construction. In the proposed strategy, by minimizing aquadratic measure of the error between desired output and the FWNN’s output, the problem is formulated as an optimizationproblem and the ABC algorithm is suggested to solve it. The structure is tested for the identification of the dynamical plants and prediction of chaotic time series. Simulation resultsdemonstrate effectiveness and ability of the proposed approach. To validate the results obtained by the proposed FWNN basedABC, a FWNN based Shuffled Frog Leaping (SFL) algorithm is adopted from the literature and applied for comparison. Thesimulation studies show ABC performs well in finding the solution.

Keywords:

Artificial bee colony algorithm , Fuzzy wavelet neural network , Identification , Prediction

Authors

Maryam Shahriari-kahkeshi

Isfahan University of Technology

Farid Sheikholeslam

Isfahan University of Technology

مراجع و منابع این Paper:

لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :