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Chaos-Enhanced Superb Fairy-wren Optimization Algorithm for Wireless Sensor Network Coverage | ||
| Journal of Algorithms and Computation | ||
| دوره 57، شماره 2، اسفند 2025، صفحه 1-24 اصل مقاله (2.61 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/jac.2025.402499.1240 | ||
| نویسندگان | ||
| Roozbeh Jalal Kamali* ؛ Mohammad Reza Omidi | ||
| Department of Computer Science, Shahid Bahonar University of kerman | ||
| چکیده | ||
| Wireless Sensor Networks (WSNs) play a crucial role in monitoring and surveillance, yet random deployment often causes uneven coverage and redundant sensing. This study introduces a Chaos-Enhanced Superb Fairy-wren Optimization Algorithm (CE-SFOA), which integrates chaotic dynamics through a Cubic map into the position update and parameter control mechanisms. The chaotic modulation enhances population diversity, balances exploration and exploitation, and mitigates premature convergence. Experiments across three deployment scenarios show that CE-SFOA consistently achieves higher coverage and faster convergence than SFOA and seven competing metaheuristics, yielding 5.32–6.65% coverage improvement over the baseline. These findings demonstrate that chaotic modulation is an effective strategy for enhancing metaheuristic performance in WSN coverage optimization. | ||
| کلیدواژهها | ||
| Coverage Optimization؛ Metaheuristic Algorithms؛ Chaos Theory؛ Swarm Intelligence؛ Chaotic Maps | ||
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آمار تعداد مشاهده مقاله: 101 تعداد دریافت فایل اصل مقاله: 60 |
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