Haul distance prediction algorithm of discrete block in open-pit mine planning stage

The ore-rock transportation distance is one of the important indexes to measure the trucking economy in open-pit mine. Due to the complex and changeable transportation system, the calculation of the each strip's transportation distance has not been effectively solved during the scheduling in the open-pit mines. In particular, when discrete material flow scheduling is needed, the traditional method of stage-by-stage transportation distance measurement cannot estimate discrete blocks one by one. Therefore, in order to effectively solve the problem of calculating the transportation distance of discrete blocks in the scheduling, the authors applies the nonlinear pre-diction theory, factor analysis method and other technical methods to the actual mine optimization problem ac-cording to the relatively fixed spatial characteristics, such as the location of the entrance and exit of the external mine dump site. The main controlling factors of the transportation fluctuation in the scheduling stage of the external dump are studied. Combined with the impact factors of the fluctuation of the transportation distance in the external dump, this paper presents an algorithm to fit the nonlinear haul distance curve using weighted least squares support vector machine (WLS-SVM). In order to improve the accuracy of the algorithm, the subjective experience indexes such as weight vector and nuclear parameter are modified dynamically to realize the fluctuation prediction of process distance. Finally, the efficient calculation of the distance between two consecutive engineering positions is realized. The experimental results show that the error of the prediction algorithm expectations are: training set is 0.93 m and test set is 0.84 m. The experiment shows the model precision is easily affected by the sample size. When the sample size N>90, the algorithm can control the absolute error level steady at between 0.8% and 1.2%. The study shows that the application of the theory of nonlinear prediction for lack of time varying network conditions to the stage's distance prediction is feasible, and the proposed algorithm model is effective in solving the problem of the assignment of discrete block in the planning stage. In the conventional open-pit mine transportation optimization problem, its optimization goal tends to have tightly coupled relationships between characteristic parameters, and the authors cannot directly apply a certain optimization, programming model to calculate. For this kind of problems, the authors try to adopt new ideas of decoupling and solving ideas for effective optimization problem, which is good for transportation problem of open-pit mine, and it should also be a hot research topic in open-pit mine system engineering in the future. © 2019, Editorial Office of Journal of China Coal Society. All right reserved.