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All Journal Perfecting a Video Game with Game Metrics Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Sriwijaya Journal of Informatics and Applications
Dian Palupi Rini
Sriwijaya University
Computer Science & IT Electrical & Electronics Engineering

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Journal : Perfecting a Video Game with Game Metrics

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Balanced the Trade-offs Problem of ANFIS using Particle Swarm Optimization Dian Palupi Rini; Siti Mariyam Shamsuddin; Siti Sophiayati Yuhaniz
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 11, No 3: September 2013
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v11i3.1146

Abstract

Improving the approximation accuracy and interpretability of fuzzy systems is an important issue either in fuzzy systems theory or in its applications . It is known that simultaneous optimization both issues was the trade-offs problem, but it will improve performance of the system and avoid overtraining of data. Particle swarm optimization (PSO) is part of evolutionary algorithm that is good candidate algorithms to solve multiple optimal solution and better global search space. This paper introduces an integration of PSO dan ANFIS for optimise its learning especially for tuning membership function parameters and finding the optimal rule for better classification. The proposed method has been tested on four standard dataset from UCI machine learning i.e. Iris Flower, Haberman’s Survival Data, Balloon and Thyroid dataset. The results have shown better classification using the proposed PSO-ANFIS and the time complexity has reduced accordingly.
Co-Authors Ayu Meida Hadipurnawan Satria Nabila Febriyanti Osvari Arsalan Siti Mariyam Shamsuddin Siti Sophiayati Yuhaniz Sukemi Sukemi Widya Aprilini