विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| अफ्रीकी गिद्ध अनुकूलन एल्गोरिथम× | स्लाइम मोल्ड एल्गोरिथम× | |
|---|---|---|
| क्षेत्र | अनुकूलन | अनुकूलन |
| परिवार | Machine learning | Machine learning |
| उद्भव वर्ष | 2020 | 2020 |
| प्रवर्तक≠ | Hossein Moghdani | Shimin Li |
| प्रकार | Nature-inspired metaheuristic algorithm | Nature-inspired metaheuristic algorithm |
| मौलिक स्रोत≠ | Moghdani, H., & Salimifard, K. (2020). Volleyball player optimizer and African vultures optimization algorithms for solving global optimization problems. Applied Soft Computing, 97, 106794. link ↗ | Li, S., Chen, H., Wang, M., Heidari, A. A., & Chakraborty, S. (2020). Slime mould algorithm: A new method for stochastic optimization. Future Generation Computer Systems, 111, 300-323. DOI ↗ |
| उपनाम | AVOA | SMA |
| संबंधित≠ | 4 | 5 |
| सारांश≠ | The African Vultures Optimization Algorithm (AVOA) is a metaheuristic algorithm introduced by Moghdani and Salimifard in 2020, inspired by the search and scavenging behavior of African vultures. Vultures employ sophisticated collaborative strategies to locate carrion across vast distances, using thermal air currents and group dynamics to navigate efficiently. AVOA translates these collective hunting behaviors into an effective optimization framework. | The Slime Mould Algorithm (SMA) is a nature-inspired metaheuristic optimization technique introduced by Li et al. in 2020. It mimics the behavior of slime moulds, which spread and contract to find optimal food sources. SMA addresses complex optimization problems by simulating the adaptive foraging and spatial distribution patterns of these organisms. |
| ScholarGateडेटासेट ↗ |
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