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通过对3辆煤炭运输自卸车在2年内的月行驶里程与维修费用数据进行分析,研究了2年间维修费用的变化趋势,对比了各维修类型所耗成本占总维修费用的比例。使用MATLAB对3辆自卸车的维修费用分别建立支持向量机回归模型,并分别使用最近10、14、10个月的里程和维修费用对煤炭运输自卸车当月维修费用进行回归预测分析。经计算,3个模型的最大预测误差分别为51%、22%和33%,均方误差值的数量级在10-4~10-5之间,平方相关系数大于0.999,具有良好的拟合性能。以此模型可对下月的维修费用进行预测。
Based on the analysis of monthly driving mileage and maintenance cost data of three coal transport dump trucks in two years, the trend of maintenance costs in two years was analyzed, and the ratio of the cost of each maintenance type to the total maintenance cost was compared. Using MATLAB to establish the support vector machine regression model for the maintenance costs of the three dump trucks, respectively, and using the mileage and maintenance costs of the last 10, 14 and 10 months respectively, the regression analysis and forecasting on the monthly maintenance costs of the coal transportation dump truck were made. The maximum prediction errors of the three models are 51%, 22% and 33% respectively. The mean square error is between 10-4 ~ 10-5 and the square correlation coefficient is greater than 0.999, which shows good fitting performance . This model can be predicted next month’s maintenance costs.