.png){kind=icon}
返回
Dynamic step opposition-based learning sparrow search algorithm for UAV path planning
.png){kind=icon}
OA
AI
DOI：10.1007/s10586-024-04691-1.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper, aiming at the problems of large randomness, low convergence accuracy, and easy falling into local optimum in the application of sparrow search algorithm to UAV three-dimensional path planning, a dynamic step opposition-based learning sparrow search algorithm is proposed. The algorithm first uses a good point set in the population initialization phase to improve the quality of the initial solution;
secondly, the piecewise dynamic step size is used to optimize the update formula of the discoverer, and the extensive search is carried out in the early stage of the iteration. In the later stage, the known area is mined as much as possible to improve the search accuracy and convergence speed of the algorithm. Then, the crazy operator is integrated to optimize the predator update formula and improve the local search ability. Finally, t-distribution opposition-based learning is used to prevent the algorithm from falling into the local optimum. In this paper, the effectiveness of the improved algorithm is verified by six test functions and applied to the three-dimensional path planning of UAVs. The experimental results show that the proposed algorithm has a faster convergence speed than the traditional algorithm, and the planned path is shorter.
Keyword:
Sparrow search algorithm
Path planning
Good point set
Opposition-based learning
期刊
C
IF:
4.1
论文数:
5.1K
被引数:
7.5K
机构
暂无机构信息
引用论文
Effect of Cell-Selection on the Effective Fading Distribution in a Downlink $K$ -Tier HetNet下行链路 $K$ -Tier HetNet 中，基于小区选择的平均衰落分布效应
OAAI
OAAI分享收藏A Robot Path Planning Method Based on Improved Genetic Algorithm and Improved Dynamic Window Approach.png)
SUSTAINABILITYOAAI
SUSTAINABILITYIF3.3
OAAI分享收藏DLX-1, DLX-2, and DLX-5 expression define distinct stages of basal forebrain differentiationDLX-1，DLX-2和DLX-5表达定义了基底前脑分化的不同阶段
PREAI
分享收藏Improved Binary Symbiotic Organism Search Algorithm With Transfer Functions for Feature SelectionIEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAI分享收藏Cooperative task allocation for heterogeneous multi-UAV using multi-objective optimization algorithm基于多目标优化算法的异构多无人机协同任务分配
PREAI
分享收藏Fuzzy Hierarchical Surrogate Assists Probabilistic Particle Swarm Optimization for expensive high dimensional problem模糊分层代理辅助概率粒子群算法求解高维问题
PREAI
分享收藏
查看更多内容