Diesel Engine Performance Prediction Based on IAOA-XGBoost Algorithm
The diesel engine is a highly coupled and nonlinear complex system.To accurately predict its perform-ance and variation,a performance prediction method based on an improved arithmetic optimization algorithm and extreme gradient boosting is proposed.Given the shortcomings of the arithmetic optimization algorithm itself,it is proposed to integrate Levy flight,Gaussian mutation,and greedy strategy into the algorithm to improve its optimi-zation ability.Based on the improved arithmetic optimization algorithm,the hyperparameters of the extreme gradi-ent boosting model are optimized to improve the prediction accuracy of the model,and an effective diesel engine performance prediction method is formed.The results show that:Compared with the BP neural network,support vector machine,and unoptimized extreme gradient boosting model,the extreme gradient boosting optimized by im-proved arithmetic optimization algorithm has higher prediction accuracy,and the prediction results for specific fuel consumption,specific HC,specific CO,specific NOx and turbine front temperature show that all determination co-efficients are greater than 0.97,and the predicted values have a good correlation with the experimental values.
万方数据
维普
