Dynamic prediction of truck travel time in open pit based on HGSVMA model

Aiming at the prediction of truck travel time in the traffic flow planning of open-pit mine, a method of optimizing SVM parameters based on genetic algorithm is proposed, and the travel time prediction model of trucks in open-pit mine based on HGSVMA model is constructed, taking into account nine factors such as truck status, speed, load, road type and slope.In the experiment, the travel time of truck collected by a truck dispatching system of a large open pit mine is selected for simulation, and the HGSVMA model is compared with the prediction results of GS-SVM model, PSO-SVM model and GA-SVM model.The results show that HGSVMA model has the best prediction effect, and has a good application prospect for improving the travel time prediction of truck in open pit mine.