Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Алгоритм оптимизации китов (WOA)× | Оптимизация роем частиц (PSO)× | |
|---|---|---|
| Область | Оптимизация | Оптимизация |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2016 | 1995 |
| Автор метода≠ | Seyedali Mirjalili & Andrew Lewis | — |
| Тип≠ | Swarm-based metaheuristic | Population-based metaheuristic / swarm intelligence |
| Основополагающий источник≠ | Mirjalili, S. & Lewis, A. (2016). The Whale Optimization Algorithm. Advances in Engineering Software, 95, 51-67. DOI ↗ | Kennedy, J. & Eberhart, R. (1995). Particle Swarm Optimization. IEEE International Conference on Neural Networks (ICNN), 1942-1948. DOI ↗ |
| Другие названия | WOA, Balina Optimizasyon Algoritması (WOA), bubble-net attacking method | PSO, swarm intelligence optimization, Parçacık Sürü Optimizasyonu (PSO) |
| Связанные≠ | 5 | 6 |
| Сводка≠ | The Whale Optimization Algorithm (WOA) is a swarm-based metaheuristic introduced by Mirjalili and Lewis in 2016. It models the bubble-net hunting strategy of humpback whales, in which a group of whales spirals around prey while gradually tightening the encirclement. The algorithm balances global exploration and local exploitation through a small set of parameters and has become widely used in continuous engineering optimisation problems. | Particle Swarm Optimization (PSO) is a population-based metaheuristic algorithm introduced by Kennedy and Eberhart in 1995, inspired by the collective movement of bird flocks and fish schools. Each candidate solution — called a particle — moves through the search space by updating its velocity and position based on its own best experience and the best experience of the entire swarm, enabling fast convergence across continuous optimization problems. |
| ScholarGateНабор данных ↗ |
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