|
Canada-0-Financing 公司名錄
|
公司新聞:
- Navigation variable-based multi-objective particle swarm optimization . . .
Path planning is essential for unmanned aerial vehicles (UAVs) as it determines the path that the UAV needs to follow to complete a task This work addresses this problem by introducing a new algorithm called navigation variable-based multi-objective particle swarm optimization (NMOPSO)
- Navigation Variable-based Multi-objective Particle Swarm Optimization . . .
Path planning is essential for unmanned aerial vehicles (UAVs) as it determines the path that the UAV needs to follow to complete a task This work addresses this problem by introducing a new algorithm called navigation variable-based multi-objective particle swarm optimization (NMOPSO)
- An implementation of multi objective PSO for UAV path planning
The algorithm is described in detail in the paper: Duong, T T N , Bui, DN Phung, M D Navigation variable-based multi-objective particle swarm optimization for UAV path planning with kinematic constraints Neural Comput Applic (2025) https: doi org 10 1007 s00521-024-10945-1
- Navigation variable-based multi-objective particle swarm optimization . . .
Path planning is essential for unmanned aerial vehicles (UAVs) as it determines the path that the UAV needs to follow to complete a task This work addresses this problem by introducing a new algorithm called navigation variable-based multi-objective particle swarm optimization (NMOPSO)
- GitHub - duongpm SPSO: Spherical Vector-based Particle Swarm . . .
Details of the algorithm are described in the paper: Thi Thuy Ngan Duong, Duy-Nam Bui, Manh Duong Phung, "Navigation variable-based multi-objective particle swarm optimization for UAV path planning with kinematic constraints", Journal of Neural Computing and Applications, 2025
- Navigation variable-based multi-objective particle swarm optimization . . .
Path planning is essential for unmanned aerial vehicles (UAVs) as it determines the path that the UAV needs to follow to complete a task This work addresses this problem by introducing a new algorithm called navigation variable-based multi-objective particle swarm optimization (NMOPSO)
- Navigation variable-based multi-objective particle swarm optimization . . .
Path planning is essential for unmanned aerial vehicles (UAVs) as it determines the path that the UAV needs to follow to complete a task This work addresses this problem by introducing a new
- Multi-Goal Rapidly Exploring Random Tree With Safety and Dynamic . . .
Abstract: Cooperative path planning is gaining its importance due to the increasing demand on using multiple unmanned aerial vehicles (UAVs) for complex missions
- 2024年12月SCI-海星优化算法Starfish optimization algorithm . . .
本期介绍了一种新的生物启发的求解优化问题的元启发式算法- 海星优化算法Starfish optimization algorithm ，SFOA，算法模拟了海星的探索、捕食和再生等行为。 该算法于 2024年11月最新发表 在人工智能核心SCI期刊 Neural Computing and Applications。 海星是一种海洋无脊椎动物，属于星纲棘皮动物，通常有5条手臂和一个中央圆盘，使它们具有独特的星状外观。 SFOA主要包括勘探和开发两个阶段。 探索阶段模拟海星的探索行为，采用五维和一维搜索模式相结合的混合搜索模式，提高了计算效率，保证了搜索容量。 开发阶段模拟海星的捕食和再生行为，采用双向搜索策略和特殊运动，以保证开发的收敛性。 1 初始化。 和其他算法一样，采用随机初始化：
- Duy-Nam Bui (0009-0001-0837-4360) - ORCID
Duy-Nam Bui is currently a Ph D student in Automatic Control at the Division of Automatic Control, Department of Electrical Engineering, Linköping University, Linköping, Sweden, where he focus on the Control of Multi-agent Networks
|
|