Evolutionary multi-objective based hierarchical interval type-2 beta fuzzy system for classification problems

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Jarraya:2017:FUZZ-IEEE,

• author = "Yosra Jarraya and Souhir Bouaziz and Adel M. Alimi",
• booktitle = "2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)",
• title = "Evolutionary multi-objective based hierarchical interval type-2 beta fuzzy system for classification problems",
• year = "2017",
• abstract = "This study addresses evolutionary structure optimisation and parameter tuning processes for evolving a proposed Hierarchical interval Type-2 Beta Fuzzy System (HT2BFS). The structure learning phase is performed in a multi-objective context by applying the Multi-Objective Extended Genetic Programming (MOEGP) algorithm. This phase aims to obtain a near-optimal structure of HT2BFS taking into account the optimisation of two objectives, which are the accuracy maximization and the number of rules minimization. Moreover, a second parameter tuning phase is also performed in order to refine the parameters of the obtained near-optimal structure by applying the PSO-based Update Memory for Improved Harmony Search (PSOUM-IHS) algorithm. The system's performance is validated through two classification problems. Results prove the efficiency of the proposed approach.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/FUZZ-IEEE.2017.8015617",
• month = jul,
• notes = "Also known as \cite{8015617}",

}

Genetic Programming entries for Yosra Jarraya Souhir Bouaziz Adel M Alimi

Citations