A new bats echolocation-based algorithm for single objective optimisation
| Autor: | Nafrizuan Mat Yahya, Hyreil Anuar Kasdirin, M. Osman Tokhi |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Computer science
Cognitive Neuroscience Human echolocation 02 engineering and technology Reciprocal altruism Adaptive bats sonar algorithm 01 natural sciences Swarm intelligence Sonar Bats sonar algorithm 010305 fluids & plasmas Single objective Mathematics (miscellaneous) Rate of convergence Bats echolocation Artificial Intelligence 0103 physical sciences Convergence (routing) 0202 electrical engineering electronic engineering information engineering Benchmark (computing) Optimisation 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Algorithm Research Paper |
| Zdroj: | Evolutionary Intelligence |
| ISSN: | 1864-5917 1864-5909 |
| DOI: | 10.1007/s12065-016-0134-5 |
| Popis: | Bats sonar algorithm (BSA) as a swarm intelligence approach utilises the concept of echolocation of bats to find prey. However, the algorithm is unable to achieve good precision and fast convergence rate to the optimum solution. With this in mind, an adaptive bats sonar algorithm is introduced with new paradigms of real bats echolocation behaviour. The performance of the algorithm is validated through rigorous tests with several single objective optimisation benchmark test functions. The obtained results show that the proposed scheme outperforms the BSA in terms of accuracy and convergence speed and can be efficiently employed to solve engineering problems. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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