2015
DOI: 10.5120/19505-1103
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A Chaotic Levy Flights Bat Algorithm for Diagnosing Diabetes Mellitus

Abstract: Bat algorithm is a meta-heuristic algorithm that is based on the echolocation behavior of bats. The searching behavior of the algorithm depends on generating uniformly distributed random walks in the search space. Hence, it may suffer from being tapped in local optima. In this paper, a classification using Bat inspired algorithm with chaotic levy flight variable is proposed. The chaotic variable has set of characteristics that enable it to enrich the searching behavior and prevent the Bat algorithm from being … Show more

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Cited by 7 publications
(3 citation statements)
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“…The proposed technique was also known as Rule based Fuzzy Logic classifier (RBFL). In [ 78 ], a technique using the Bat algorithm was developed to detect diabetes mellitus. The technique had the special feature of avoiding the solution being trapped in the local optimum instead of searching for optimum global values.…”
Section: Related Workmentioning
confidence: 99%
“…The proposed technique was also known as Rule based Fuzzy Logic classifier (RBFL). In [ 78 ], a technique using the Bat algorithm was developed to detect diabetes mellitus. The technique had the special feature of avoiding the solution being trapped in the local optimum instead of searching for optimum global values.…”
Section: Related Workmentioning
confidence: 99%
“…The BA metaheuristic has already been successfully applied to several problem domains. On the one hand, to continuous optimization problems like economic load dispatch problem [40], parameter estimation [41], diagnosing diseases [42]. On the other hand, to discrete/combinatorial optimization problems like traveling salesman problem [43], job shop scheduling [44], patient bed assignment problem [45], or human pose estimation [46].…”
Section: Application Areas Of Bat Algorithmmentioning
confidence: 99%
“…GONN have the uppermost accuracy of 98.24%, 99.63%, 100% for 50-50, 60-40 and 70% training dataset and 30% test dataset partitions respectively and 10-fold cross-validation for 50 Genetic programming runs for 1-1-1 neural network as 100% accuracy. Limitation of this approach was that only crossover and mutation operators were improved and other areas like Omar S. Soliman and Eman Abo ElHamd [6] proposed an algorithm based on chaotic levy flights bat algorithm for diagnosing diabetes mellitus. In swarm intelligence, different types of metaheuristics or natured inspired algorithms are present.…”
Section: Introductionmentioning
confidence: 99%