A Modified Bio Inspired: BAT Algorithm

Metaheuristics algorithms are becoming powerful methods for solving many problems of market analysis, data mining, transportation, medical etc. The concept of BAT algorithm, particle swarm optimization, artificial bee colony optimization, cuckoo search, firefly algorithm and harmony search are power...

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Published inInternational journal of applied metaheuristic computing Vol. 9; no. 1; pp. 60 - 77
Main Author Singh, Dharmpal
Format Journal Article
LanguageEnglish
Published Hershey IGI Global 01.01.2018
Subjects
Accuracy
Algorithms
Analysis
Artificial intelligence
Benchmarks
Breast cancer
Chi-square test
Concrete
Data mining
Datasets
Diabetes
Echolocation (Physiology)
Heuristic methods
Integer programming
Investment analysis
Knowledge discovery
Machine learning
Optimization
Particle swarm optimization
Search algorithms
Statistical methods
Swarm intelligence
Wisconsin
Online AccessGet full text
ISSN1947-8283
1947-8291
DOI10.4018/IJAMC.2018010105

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Abstract Metaheuristics algorithms are becoming powerful methods for solving many problems of market analysis, data mining, transportation, medical etc. The concept of BAT algorithm, particle swarm optimization, artificial bee colony optimization, cuckoo search, firefly algorithm and harmony search are powerful methods for solving many optimization problems. Here, an effort has been made to propose as modified form of the BAT algorithm based natural echolocation behaviour of bats to solve the optimization problems. The algorithm is also compared other 15 existing benchmark algorithms including statistical methods on five benchmarks data sets. Furthermore, modified BAT algorithm has outperformed the other algorithm in term of robustness and efficiency. The optimality of the algorithm has been also crosscheck with residual analysis and chi (χ2) square testing.
AbstractList Metaheuristics algorithms are becoming powerful methods for solving many problems of market analysis, data mining, transportation, medical etc. The concept of BAT algorithm, particle swarm optimization, artificial bee colony optimization, cuckoo search, firefly algorithm and harmony search are powerful methods for solving many optimization problems. Here, an effort has been made to propose as modified form of the BAT algorithm based natural echolocation behaviour of bats to solve the optimization problems. The algorithm is also compared other 15 existing benchmark algorithms including statistical methods on five benchmarks data sets. Furthermore, modified BAT algorithm has outperformed the other algorithm in term of robustness and efficiency. The optimality of the algorithm has been also crosscheck with residual analysis and chi (χ2) square testing.
Audience Academic
Author Singh, Dharmpal
AuthorAffiliation CSE Department, JIS College of Engineering, Kalyani, India
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Copyright COPYRIGHT 2018 IGI Global
Copyright © 2018, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
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Snippet Metaheuristics algorithms are becoming powerful methods for solving many problems of market analysis, data mining, transportation, medical etc. The concept of...
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SubjectTerms Accuracy
Algorithms
Analysis
Artificial intelligence
Benchmarks
Breast cancer
Chi-square test
Concrete
Data mining
Datasets
Diabetes
Echolocation (Physiology)
Heuristic methods
Integer programming
Investment analysis
Knowledge discovery
Machine learning
Optimization
Particle swarm optimization
Search algorithms
Statistical methods
Swarm intelligence
Title A Modified Bio Inspired: BAT Algorithm
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