现代防御技术2025，Vol.53Issue(3)：74-81,8.DOI:10.3969/j.issn.1009-086x.2025.03.009
基于BOA-BP神经网络的四旋翼飞行器路径优化
Optimization of Path Error for Quadcopter Based on BOA-BP Neural Network
摘要
Abstract
An optimization method for BP neural networks based on the butterfly optimization algorithm(BOA)is proposed to address the issue of inaccurate path planning for quadcopters in multi-obstacle environments.The points of the quadcopter along the designated path are used as training samples for the neural network,and the BOA-BP algorithm is employed to train the network to determine the optimal flight path.The simulation results show that the proposed BOA-BP model effectively reduces the path error of the quadcopter compared to the traditional BOA algorithm,with the root mean square error decreasing from 1.60％to 0.003％.关键词
四旋翼/飞行器/蝴蝶优化算法/BP神经网络/路径优化/训练样本/误差处理Key words
quadcopter/aircraft/butterfly optimization algorithm(BOA)/back propagation(BP)neural network/path optimization/training sample/error processing分类
机械制造引用本文复制引用
王舒玮,李嘉,冯健,岳彩宾..基于BOA-BP神经网络的四旋翼飞行器路径优化[J].现代防御技术,2025,53(3):74-81,8.基金项目
山西省基础研究计划(202103021224313) （202103021224313）
山西大同大学2021年度科研专项课题项目(2021YGZX53) （2021YGZX53）
山西省高等学校科技创新项目(2024L321). （2024L321）
