Dipper Throated Optimization Algorithm for Unconstrained Function and Feature Selection

Dipper throated optimization (DTO) algorithm is a novel with a very efficient metaheuristic inspired by the dipper throated bird. DTO has its unique hunting technique by performing rapid bowing movements. To show the efficiency of the proposed algorithm, DTO is tested and compared to the algorithms...

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Vydáno v:Computers, materials & continua Ročník 72; číslo 1; s. 1465 - 1481
Hlavní autoři: E. Takieldeen, Ali, M. El-kenawy, El-Sayed, Hadwan, Mohammed, M. Zaki, Rokaia
Médium: Journal Article
Jazyk:angličtina
Vydáno: Henderson Tech Science Press 2022
Témata:
Bowing
Dipping
Feature selection
Genetic algorithms
Heuristic methods
Optimization algorithms
Optimization techniques
Particle swarm optimization
ISSN:1546-2226, 1546-2218, 1546-2226
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Shrnutí:Dipper throated optimization (DTO) algorithm is a novel with a very efficient metaheuristic inspired by the dipper throated bird. DTO has its unique hunting technique by performing rapid bowing movements. To show the efficiency of the proposed algorithm, DTO is tested and compared to the algorithms of Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), Grey Wolf Optimizer (GWO), and Genetic Algorithm (GA) based on the seven unimodal benchmark functions. Then, ANOVA and Wilcoxon rank-sum tests are performed to confirm the effectiveness of the DTO compared to other optimization techniques. Additionally, to demonstrate the proposed algorithm's suitability for solving complex real-world issues, DTO is used to solve the feature selection problem. The strategy of using DTOs as feature selection is evaluated using commonly used data sets from the University of California at Irvine (UCI) repository. The findings indicate that the DTO outperforms all other algorithms in addressing feature selection issues, demonstrating the proposed algorithm's capabilities to solve complex real-world situations.
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ISSN:1546-2226
1546-2218
1546-2226
DOI:10.32604/cmc.2022.026026