ScholarGate
Asistenti

Krahasoni metodat

Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.

Optimizuesi Aquila×Optimizimi i Shpendit Harris×
FushaOptimizimiOptimizimi
FamiljaMachine learningMachine learning
Viti i origjinës20212019
KrijuesiLaith AbualigahAli Asghar Heidari
LlojiNature-inspired metaheuristic algorithmNature-inspired metaheuristic algorithm
Burimi themeluesAbualigah, L., Yousri, D., Abd Elaziz, M., Ewees, A. A., Al-qaness, M. A., & Gandomi, A. H. (2021). Aquila optimizer: A novel meta-heuristic optimization algorithm. Computers and Industrial Engineering, 157, 107250. DOI ↗Heidari, A. A., Mirjalili, S., Faris, H., Aljarah, I., Mafarja, M., & Chen, H. (2019). Harris hawks optimization: Algorithm and applications. Future Generation Computer Systems, 97, 849-872. DOI ↗
Emërtime të tjeraAOHHO
Të lidhura34
PërmbledhjaThe Aquila Optimizer (AO) is a nature-inspired metaheuristic algorithm presented by Abualigah et al. in 2021, modeled after the hunting behavior and sensory abilities of golden eagles (aquila chrysaetos). The algorithm captures the exploration and exploitation phases of eagle hunting, including high-altitude soaring, exploration with high-precision vision, and rapid diving attacks. AO is designed to solve both constrained and unconstrained optimization problems.Harris Hawks Optimization (HHO) is a metaheuristic algorithm introduced by Heidari et al. in 2019, inspired by the hunting strategies of Harris's hawks. The algorithm models the cooperative hunting behavior and escape strategies of these raptors to solve complex optimization problems. HHO balances exploration through perching and exploitation through dynamic pursuit, making it effective for multimodal and high-dimensional optimization.
ScholarGateSeti i të dhënave
  1. v1
  2. 1 Burimet
  3. PUBLISHED
  1. v1
  2. 1 Burimet
  3. PUBLISHED

Shko te kërkimi Shkarko diapozitivat

ScholarGateKrahasoni metodat: Aquila Optimizer · Harris Hawks Optimization. Marrë më 2026-06-18 nga https://scholargate.app/sq/compare