Multimedia Systems, Journal Year: 2024, Volume and Issue: 30(5)
Published: Aug. 30, 2024
Language: Английский
Multimedia Systems, Journal Year: 2024, Volume and Issue: 30(5)
Published: Aug. 30, 2024
Language: Английский
Energy, Journal Year: 2024, Volume and Issue: unknown, P. 133894 - 133894
Published: Nov. 1, 2024
Language: Английский
Citations
1Discover Geoscience, Journal Year: 2024, Volume and Issue: 2(1)
Published: Oct. 24, 2024
The use of nature-inspired meta-heuristics to tackle complex optimization problems is steadily gaining popularity within a rapidly evolving world. Swarm intelligence (SI) motivated by behavior community-based organisms flocks birds, schools fish, colonies ants and bees performs the search through agents whose trajectories are primarily adjusted stochastically sporadically deterministically, golden rules drawn from Mother Nature. Each entity swarm swayed its individual 'best' group's position while moving randomly converge optimal competition cooperation. sparrow algorithm (SSA), developed Xuea Shen (Xue in Syst Sci Cont Eng 8:22–34, 2020) very recent SI approach that adopts producer–scrounger model metaphorically for designing optimum searching strategies, inspired foraging, anti-predation behavior, overall group wisdom sparrows. SSA has been experimented on some hard benchmark test functions effectiveness thereafter, applied slope-stability critical failure surface. objective function be optimized factor safety against given Bishop's (Bishop Geotechnique 5:7–17, 1955) simplified method. Results show strong contender bio-inspired methods like genetic algorithms, big-bang big-crunch, simulated annealing, artificial bee colony algorithms. study illustrates flexibility, efficiency, robustness methodology optimization.
Language: Английский
Citations
1Multimedia Systems, Journal Year: 2024, Volume and Issue: 30(5)
Published: Aug. 30, 2024
Language: Английский
Citations
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