机械与电子2025，Vol.43Issue(12)：68-72,80,6.
基于海洋捕食算法优化随机森林的直升机吊挂载荷拉力预测
Pull Prediction of Helicopter Slung Load Based on Random Forest Optimized by Marine Predators Algorithm
摘要
Abstract
Due to the influence of multi-source nonlinear coupling such as downwash flow,attitude change of the hanging load and wind disturbance,it is difficult to achieve real-time and high-precision prediction of the tension force of the hanging load when the helicopter is hovering,which affects the flight safety of the helicopter.To solve the problem,a random forest algorithm optimized by Marine Predators Algorithm is proposed to predict the tension force of the hanging load.Firstly,the experimental data are collected and the random forest regression model is constructed;then,the root mean square error of the training set is used as the fitness function,and the marine predators algorithm is used to globally optimize the number of trees and the maximum depth to obtain the optimal model parameters;finally,the optimized model is applied to the test set to achieve high-precision prediction of the sling tension.Simulation and ex-perimental results show that the prediction accuracy of the random forest model optimized by the Marine Predators Algorithm is as high as 97.85%,which verifies the efficiency and reliability of the method and provides solid data support for the subsequent online adaptive control strategy.关键词
直升机/吊挂载荷/RF算法/MPA算法/拉力预测Key words
helicopter/hanging load/RF algorithm/MPA algorithm/pull prediction分类
航空航天引用本文复制引用
陆子怡,何建,刘毅臻..基于海洋捕食算法优化随机森林的直升机吊挂载荷拉力预测[J].机械与电子,2025,43(12):68-72,80,6.基金项目
大学生创新创业训练计划项目(S202410624165) （S202410624165）
