In recent years, the frequency of weather-related natural disasters—cyclones, torrential rains, floods—has increased as a ...
Black-box optimization, particularly Bayesian optimization, is a practical approach for weather-intervention design, achieving meaningful rainfall ...
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Explorative PSO for drone swarms in occluded target tracking
In complex environments such as dense forests, detecting and tracking moving targets presents significant challenges due to ...
By 2050, urban centers will house nearly 70% of the global population. Transitioning to localized food production via Urban Agriculture (UA) including ...
A research team has developed an optimized energy management strategy for a hybrid residential microgrid that combines solar ...
Using a Particle Swarm Optimization (PSO) algorithm, the study found that coordinated sizing and dispatch of distributed energy resources can ...
Toy Story 5 opened June 19 to a $164 million weekend by making its villain a real AI failure mode — goal misgeneralization, where measurable proxies like friend counts diverge from the human value ...
The purpose of swarm is to provide a novel clustering algorithm that handles massive sets of amplicons. Results of traditional clustering algorithms are strongly input-order dependent, and rely on an ...
Abstract: This paper concerns the multi-UAV task assignment problem, which is solved by a multi-objective particle swarm optimization algorithm for adaptive region partitioning. Since the traditional ...
Abstract: This article presents a hybrid metaheuristic optimization algorithm that combines particle filter (PF) and particle swarm optimization (PSO) algorithms. The new PF–PSO algorithm consists of ...
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