顾清华, 马平平, 闫宝霞, 卢才武, 陈露. 基于HGSVMA模型的露天矿卡车行程时间动态预测研究[J]. 中国矿业, 2021, 30(4): 96-102. DOI: 10.12075/j.issn.1004-4051.2021.04.015
    引用本文: 顾清华, 马平平, 闫宝霞, 卢才武, 陈露. 基于HGSVMA模型的露天矿卡车行程时间动态预测研究[J]. 中国矿业, 2021, 30(4): 96-102. DOI: 10.12075/j.issn.1004-4051.2021.04.015
    GU Qinghua, MA Pingping, YAN Baoxia, LU Caiwu, CHEN Lu. Dynamic prediction of truck travel time in open pit based on HGSVMA model[J]. CHINA MINING MAGAZINE, 2021, 30(4): 96-102. DOI: 10.12075/j.issn.1004-4051.2021.04.015
    Citation: GU Qinghua, MA Pingping, YAN Baoxia, LU Caiwu, CHEN Lu. Dynamic prediction of truck travel time in open pit based on HGSVMA model[J]. CHINA MINING MAGAZINE, 2021, 30(4): 96-102. DOI: 10.12075/j.issn.1004-4051.2021.04.015

    基于HGSVMA模型的露天矿卡车行程时间动态预测研究

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

    • 摘要: 针对露天矿卡车在车流规划中的行驶时间预测问题,提出一种基于遗传算法优化SVM参数方法,并考虑卡车状态、速度、载重量以及路面类型、坡度等9个影响因子,构建了基于HGSVMA模型的露天矿卡车行程时间预测模型。实验选取某大型露天矿卡车调度系统所采集的卡车行程时间进行仿真模拟,并将HGSVMA模型与GS-SVM模型、PSO-SVM模型和GA-SVM模型的预测结果进行对比,结果表明,HGSVMA模型预测效果最好,对提高露天矿卡车行程时间预测具有良好的应用前景。

       

      Abstract: 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.

       

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