Applied Intelligence, Journal Year: 2024, Volume and Issue: 55(1)
Published: Dec. 5, 2024
Language: Английский
Results in Engineering, Journal Year: 2024, Volume and Issue: 22, P. 102195 - 102195
Published: May 3, 2024
This article presents a heuristic methodology to address the operation problem of PV-STATCOMs, focusing on dynamic compensation active and reactive power minimize daily energy losses costs associated with purchasing in distribution networks. The is developed using master-slave type optimization approach. In master stage, potential solutions are generated an algorithm based salp swarm. contrast, slave stage evaluates these flow method by successive approximations. was evaluated two IEEE test systems, 33 69 nodes, varying factor each PV-STATCOM. results demonstrate significant reduction both network cost at substation. Furthermore, efficiency swarm for effective resolution confirmed. approach contributes optimizing PV-STATCOMs highlights proposed algorithm's applicability effectiveness practical environments.
Language: Английский
Citations
14
Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)
Published: Feb. 6, 2025
The Snow Goose Algorithm (SGA) is a new meta-heuristic algorithm proposed in 2024, which has been proved to have good optimization effect, but there are still problems that easy fall into local optimal and premature convergence. In order further improve the performance of algorithm, this paper proposes an improved (ISGA) based on three strategies according real migration habits snow geese: (1) Lead goose rotation mechanism. (2) Honk-guiding (3) Outlier boundary strategy. Through above strategies, exploration development ability original comprehensively enhanced, convergence accuracy speed improved. paper, two standard test sets IEEE CEC2022 CEC2017 used verify excellent algorithm. practical application ISGA tested through 8 engineering problems, employed enhance effect clustering results show compared with comparison faster iteration can find better solutions, shows its great potential solving problems.
Language: Английский
Citations
1
iScience, Journal Year: 2024, Volume and Issue: 27(8), P. 110561 - 110561
Published: July 22, 2024
Rime optimization algorithm (RIME) encounters issues such as an imbalance between exploitation and exploration, susceptibility to local optima, low convergence accuracy when handling problems. This paper introduces a variant of RIME called IRIME address these drawbacks. integrates the soft besiege (SB) composite mutation strategy (CMS) restart (RS). To comprehensively validate IRIME's performance, IEEE CEC 2017 benchmark tests were conducted, comparing it against many advanced algorithms. The results indicate that performance is best. In addition, applying in four engineering problems reflects solving practical Finally, proposes binary version, bIRIME, can be applied feature selection bIRIMR performs well on 12 low-dimensional datasets 24 high-dimensional datasets. It outperforms other algorithms terms number subsets classification accuracy. conclusion, bIRIME has great potential selection.
Language: Английский
Citations
4
Applied Soft Computing, Journal Year: 2025, Volume and Issue: unknown, P. 112753 - 112753
Published: Jan. 1, 2025
Language: Английский
Citations
0
The Journal of Supercomputing, Journal Year: 2025, Volume and Issue: 81(5)
Published: April 4, 2025
Language: Английский
Citations
0
The Journal of Supercomputing, Journal Year: 2024, Volume and Issue: 81(1)
Published: Oct. 28, 2024
Language: Английский
Citations
3
Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)
Published: Oct. 29, 2024
Tackling the shortcomings of slow convergence, imprecision, and entrapment in local optima inherent traditional meta-heuristic algorithms, this study presents enhanced artificial hummingbird algorithm with chaotic traversal flight (CEAHA), which employs ergodicity within foundational framework conventional algorithm. This approach implements motion regions solution space, ensuring a thorough exploration potential preventing algorithmic stagnation at maxima by guaranteeing non-repetitive all search states. also analyzes intrinsic mechanisms eight different mappings affect optimization performance, from perspectives invariant measures efficiency ergodic motion. In comparative tests 21 algorithms on CEC2014, CEC2019, CEC2022 benchmark suites across various dimensions, CEAHA demonstrates superior performance. Furthermore, practicability robustness have been confirmed mechanical design problems through 4 engineering instances: pressure vessel, gear trains, speed reducers, piston levers.
Language: Английский
Citations
1
Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown
Published: Feb. 16, 2024
Abstract Rime optimization algorithm (RIME) is an emerging metaheuristic algorithm. However, RIME encounters issues such as imbalance between exploitation and exploration, susceptibility to local optima, low convergence accuracy when handling problems. To address these drawbacks, this paper introduces a variant of called IRIME. IRIME integrates the soft besiege (SB) composite mutation strategy restart (CMS-RS), aiming balance exploration in RIME, enhance population diversity, improve accuracy, endow with capability escape optima. comprehensively validate IRIME's performance, IEEE CEC 2017 benchmark tests were conducted, comparing it against 13 conventional algorithms 11 advanced algorithms, including excellent competition JADE. The results indicate that performance best. practical applicability, proposes binary version, bIRIME, applied feature selection bIRIMR performs well on 12 low-dimensional datasets 24 high-dimensional datasets. It outperforms other terms number subsets classification accuracy. In conclusion, bIRIME notably selection, particularly
Language: Английский
Citations
0
Applied Intelligence, Journal Year: 2024, Volume and Issue: 55(1)
Published: Dec. 5, 2024
Language: Английский
Citations
0