Abstract
ABSTRACTA new improved shuffled frog leaping algorithm (SFLA), the chaos catfish effect SFLA (CCESFLA), is proposed by coupling a local “refine search” mechanism and a “global incentive adjustment” mechanism. Chaotic technology is introduced in the local “refine search” mechanism to improve local search ability, by implementing more refined local search around the optimal individuals. The catfish effect mechanism is adopted in the “global incentive adjustment” mechanism to improve global convergence, by motivating the frogs to “jump out” of the local steady state. The operation optimization by the CCESFLA is carried out taking the Li Xianjiang cascade reservoirs in China as an example. Compared with SFLA, particle swarm optimization, immune SFLA and cloud SFLA, the average annual power generation using the CCESFLA can be increased by 6.7, 7.5, 3.0 and 0.8%, respectively. The convergence process of the CCESFLA is more stable, and its execution time is the least of the three improved SFLAs.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
