Research on Civil Aviation Accident Classification Model Based on Improved Raccoon Algorithm Optimized Random Forest
In order to improve the computational performance and robustness of the random forest model,and overcome the adverse effects of parameter selection on the performance of the random forest model,this study uses the improved raccoon algorithm(ICOA)to optimize the random forest model(RF),establishes the ICOA-RF model,and applies the ICOA-RF hybrid model to validate the classification of accidents in civil aviation history.The results show that:the raccoon algorithm is improved by wavelet function perturbation strategy and mutualistic symbiosis strategy,which improves the searching ability of the raccoon algorithm and increases the diversity of the populations,avoids blind searching,and improves the overall solution accuracy of the algorithm;the ICOA-RF model fits the civil aviation historical accident data better,and the classification accuracy is good.It can be seen that the ICOA-RF model has a strong global optimization ability,the classification accuracy meets the requirements,and the model can be used for the classification of civil aviation accidents.
wavelet function perturbation strategymutual benefit and symbiosis strategyraccoon algorithmrandom forestmodel optimizationclassification of civil aviation accidents
万方数据
维普
