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An improved bees algorithm local search mechanism for numerical dataset

Al-Dawoodi, Aras Ghazi Mohammed (2015) An improved bees algorithm local search mechanism for numerical dataset. Masters thesis, Universiti Utara Malaysia.

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Abstract

Bees Algorithm (BA), a heuristic optimization procedure, represents one of the fundamental search techniques is based on the food foraging activities of bees. This algorithm performs a kind of exploitative neighbourhoods search combined with random explorative search. However, the main issue of BA is that it requires long computational time as well as numerous computational processes to obtain a good solution, especially in more complicated issues. This approach does not guarantee any optimum solutions for the problem mainly because of lack of accuracy. To solve this issue, the local search in the BA is investigated by Simple swap, 2-Opt and 3-Opt were proposed as Massudi methods for Bees Algorithm Feature Selection (BAFS). In this study, the proposed extension methods is 4-Opt as search neighbourhood is presented. This proposal was implemented and comprehensively compares and analyse their performances with respect to accuracy and time. Furthermore, in this study the feature selection algorithm is implemented and tested using most popular dataset from Machine Learning Repository (UCI). The obtained results from experimental work confirmed that the proposed extension of the search neighbourhood including 4-Opt approach has provided better accuracy with suitable time than the Massudi methods.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Bees Algorithm (BA), Feature selection, Local search, Simple swap, 2-Opt and 3-Opt, 4-Opt approaches.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Awang Had Salleh Graduate School of Arts & Sciences
Depositing User: Mr. Badrulsaman Hamid
Date Deposited: 16 May 2016 09:21
Last Modified: 03 Jun 2018 08:33
URI: http://etd.uum.edu.my/id/eprint/5622

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