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An Improved BSA with Dynamic Grouping Strategy and Its Application in UAV Path Planning

Year: 2024

Type: article

Abstract: Due to the issues of slow convergence speed and low accuracy in swarm intelligence algorithms for UAV path planning, this paper proposes An Improved Bird Swarm Algorithm with dynamic grouping strategy(DGSBSA).This method introduces strategies such as dynamic grouping and reverse foraging to enhance the algorithm's performance.During the iteration process, dynamic grouping is performed based on the positions of the bird swarm to enhance population diversity.The experimental results demonstrate that the proposed DGSBSA algorithm improves the algorithm's accuracy and enhances the convergence speed in the path planning process.

Source: Mathematical Modeling and Algorithm Application

DOI: 10.54097/38mpj028

Author: Zirui Zhao

Language: English

Topic: Metaheuristic Optimization Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4405040799

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