Computer Methods in Applied Mechanics and Engineering, Год журнала: 2023, Номер 415, С. 116199 - 116199
Опубликована: Июль 19, 2023
Язык: Английский
IEEE Access, Год журнала: 2022, Номер 10, С. 49445 - 49473
Опубликована: Янв. 1, 2022
In this paper, a new bio-inspired metaheuristic algorithm called Zebra Optimization Algorithm (ZOA) is developed; its fundamental inspiration the behavior of zebras in nature. ZOA simulates foraging and their defense strategy against predators' attacks. The steps are described then mathematically modeled. performance optimization evaluated on sixty-eight benchmark functions, including unimodal, high-dimensional multimodal, fixed-dimensional CEC2015, CEC2017. results obtained from compared with nine well-known algorithms. simulation show that can solve problems by creating suitable balance between exploration exploitation has superior to competitor ZOA's ability real-world been tested four engineering design problems, namely, tension/compression spring, welded beam, speed reducer, pressure vessel. an effective optimizer determining values variables these
Язык: Английский
Процитировано
252
Knowledge-Based Systems, Год журнала: 2023, Номер 262, С. 110248 - 110248
Опубликована: Янв. 3, 2023
Язык: Английский
Процитировано
237
Archives of Computational Methods in Engineering, Год журнала: 2022, Номер 30(1), С. 427 - 455
Опубликована: Авг. 22, 2022
Язык: Английский
Процитировано
229
Computers in Biology and Medicine, Год журнала: 2022, Номер 148, С. 105858 - 105858
Опубликована: Июль 16, 2022
Язык: Английский
Процитировано
212
Artificial Intelligence Review, Год журнала: 2023, Номер 56(10), С. 11675 - 11738
Опубликована: Март 13, 2023
Язык: Английский
Процитировано
178
Artificial Intelligence Review, Год журнала: 2022, Номер 56(6), С. 5479 - 5543
Опубликована: Ноя. 2, 2022
Язык: Английский
Процитировано
137
Archives of Computational Methods in Engineering, Год журнала: 2023, Номер 30(7), С. 4113 - 4159
Опубликована: Май 27, 2023
Язык: Английский
Процитировано
122
Artificial Intelligence Review, Год журнала: 2024, Номер 57(4)
Опубликована: Март 23, 2024
Abstract This paper innovatively proposes the Black Kite Algorithm (BKA), a meta-heuristic optimization algorithm inspired by migratory and predatory behavior of black kite. The BKA integrates Cauchy mutation strategy Leader to enhance global search capability convergence speed algorithm. novel combination achieves good balance between exploring solutions utilizing local information. Against standard test function sets CEC-2022 CEC-2017, as well other complex functions, attained best performance in 66.7, 72.4 77.8% cases, respectively. effectiveness is validated through detailed analysis statistical comparisons. Moreover, its application solving five practical engineering design problems demonstrates potential addressing constrained challenges real world indicates that it has significant competitive strength comparison with existing techniques. In summary, proven value advantages variety due excellent performance. source code publicly available at https://www.mathworks.com/matlabcentral/fileexchange/161401-black-winged-kite-algorithm-bka .
Язык: Английский
Процитировано
113
Mathematics, Год журнала: 2022, Номер 10(19), С. 3466 - 3466
Опубликована: Сен. 23, 2022
This paper introduces a novel physical-inspired metaheuristic algorithm called “Light Spectrum Optimizer (LSO)” for continuous optimization problems. The inspiration the proposed is light dispersions with different angles while passing through rain droplets, causing meteorological phenomenon of colorful rainbow spectrum. In order to validate algorithm, three experiments are conducted. First, LSO tested on solving CEC 2005, and obtained results compared wide range well-regarded metaheuristics. second experiment, used four competitions in single objective benchmarks (CEC2014, CEC2017, CEC2020, CEC2022), its eleven well-established recently-published optimizers, named grey wolf optimizer (GWO), whale (WOA), salp swarm (SSA), evolutionary algorithms like differential evolution (DE), optimizers including gradient-based (GBO), artificial gorilla troops (GTO), Runge–Kutta method (RUN) beyond metaphor, African vultures (AVOA), equilibrium (EO), Reptile Search Algorithm (RSA), slime mold (SMA). addition, several engineering design problems solved, many from literature. experimental statistical analysis demonstrate merits highly superior performance algorithm.
Язык: Английский
Процитировано
112
Electronics, Год журнала: 2022, Номер 11(22), С. 3798 - 3798
Опубликована: Ноя. 18, 2022
Developing countries have had numerous obstacles in diagnosing the COVID-19 worldwide pandemic since its emergence. One of most important ways to control spread this disease begins with early detection, which allows that isolation and treatment could perhaps be started. According recent results, chest X-ray scans provide information about onset infection, may evaluated so diagnosis can begin sooner. This is where artificial intelligence collides skilled clinicians’ diagnostic abilities. The suggested study’s goal make a contribution battling epidemic by using simple convolutional neural network (CNN) model construct an automated image analysis framework for recognizing afflicted data. To improve classification accuracy, fully connected layers CNN were replaced efficient extreme gradient boosting (XGBoost) classifier, used categorize extracted features layers. Additionally, hybrid version arithmetic optimization algorithm (AOA), also developed facilitate proposed research, tune XGBoost hyperparameters images. Reported experimental data showed approach outperforms other state-of-the-art methods, including cutting-edge metaheuristics algorithms, tested same framework. For validation purposes, balanced images dataset 12,000 observations, belonging normal, viral pneumonia classes, was used. method, tuned introduced AOA, superior performance, achieving accuracy approximately 99.39% weighted average precision, recall F1-score 0.993889, 0.993887 0.993887, respectively.
Язык: Английский
Процитировано
110