Research On Scheduling Services Of Open-pit Mine Based On Real-time Travel Time Prediction

GNSS/GIS and wireless communication technology cut the cost of opencastscheduling system, and also reduce the interaction barriers between staff and thesystem. According to the analysis of law of travel time changes of each car on everypath, comparatively studying on the results of BP neural network and support vectormachine in the travel time prediction, we build a SVM model to predict the traveltime of a vehicle on the path in the next stage. The result shows that the dynamicscheduling model can be improved by the travel time predicted; A new parameter isbrought into the dynamic scheduling algorithm to reduce the frequency of pathchanges for a vehicle. A new server architecture is proposed based on the theory ofserver flow and cloud computing, and this also reduce the cost of whole system.Finally, we build a scheduling business processes and vehicle terminal businessprocesses based on theory of workflow using Petri network, and calculate thetime-consuming of transportation system business processes based on equivalent timecomputing theory, quantitatively analyze the change of transportation system businessprocesses in open-pit mine.