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Journals / International Journal of Intelligent Systems and Applications in Engineering / 2016 / Cilt: 4 Sayı: Special Issue-1 Özel Sayı

Training ANFIS Using Genetic Algorithm for Dynamic Systems Identification

Bülent Haznedar(HASAN KALYONCU ÜNİVERSİTESİ)
Adem Kalınlı(ERCİYES ÜNİVERSİTESİ)
Pages
44–47
Publication Date
2016-12-26
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

With this study it was observed that the optimisation of ANFIS parameters using GA is more successful than the other methods.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, the premise and consequent parameters of ANFIS are optimized using Genetic Algorithm (GA) based on a population algorithm.
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Key Findings & Data:The proposed approach is applied to the nonlinear dynamic system identification problem.
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Conclusion & Impact:With this study it was observed that the optimisation of ANFIS parameters using GA is more successful than the other methods.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Neuro-Fuzzy · ANFIS · Genetic Algorithm

Abstract

In this study, the premise and consequent parameters of ANFIS are optimized using Genetic Algorithm (GA) based on a population algorithm. The proposed approach is applied to the nonlinear dynamic system identification problem. The simulation results of the method are compared with the Backpropagation (BP) algorithm and the results of other methods that are available in the literature. With this study it was observed that the optimisation of ANFIS parameters using GA is more successful than the other methods.

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Cite This Article

Haznedar, B., Kalınlı, A. (2016). Training ANFIS Using Genetic Algorithm for Dynamic Systems Identification. International Journal of Intelligent Systems and Applications in Engineering, Cilt: 4 Sayı: Special Issue-1 Özel Sayı, 44–47. https://doi.org/10.18201/ijisae.266053

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