id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
cana-827	Yatish SJ	Optimizing Forest Surveillance: A Hybrid Algorithm Combining ACO and ABC	2024	19	.pdf	application/pdf	7368	430	44	No. 4s (2024) 33 https://internationalpubls.com Table 1 represents the Performace of ACO algorithm in drone Surveillance for the Scenario 1 and 2 Path Length: ACO finds relatively efficient routes for drone surveillance missions, as seen by its moderate path length optimization. Analysis of ABC in swarm of drone Surveillance using performance metrics, statistical values, and the efficiency of the algorithms Fig 3 represents the swarm in surveillance using ABC optimization Metric Performance (mean ± standard deviation) Efficiency Path Length (units) 950 ± 75 Improved Flight Time (minutes) 42 ± 4 Improved Energy Consumption (kWh) 11 ± 1 Improved Convergence Speed 100 iterations Improved Solution Quality 92% optimal solutions Very Good Robustness Resilient to varying conditions Very Good Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 31 No. 4s (2024) 34 https://internationalpubls.com Scalability Effective for various scenarios Very Good Resource Usage Low CPU and memory usage Very Good Table 2 represents the Performace of ABC algorithm in drone Surveillance for the Fig 3 Path Length: ABC regularly finds shorter and more effective paths for drone surveillance missions, demonstrating enhanced path length optimization.	cache/cana-827.pdf	txt/cana-827.txt