利用二阶多项式回归预测胶结膏体充填体抗拉强度

Q. T. Ngo, L. Nguyen, Quan Van Tran
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引用次数: 0

摘要

将矿石中有价值的部分与无利可图的部分分离后留下的物质在采矿业中被称为尾矿。将尾砂、水泥和水混合可以产生一种称为胶结膏体回填(CPB)的新材料。研究并解决了基于多项式模型与蒙特卡罗模拟法相结合的水泥浆体充填体抗拉强度预测问题。建立了三个模型来评估性能。利用最优性能模型对水泥膏体充填体抗拉强度进行预测。结果表明,采用多项式回归模型对水泥浆体充填体抗拉强度进行预测具有较好的效果。采用R2=0.958 RMSE=33.211 kPa MAE=29.097 kPa 3个指标评价二阶多项式回归模型在预测胶结膏体充填体抗拉强度方面的最佳性能。最后,借助二阶多项式回归模型的最佳性能,评价了灰尾料比和固含量对抗拉强度的影响、抗拉强度和重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting tensile strength of cemented paste backfill with aid of second order polynomial regression
The materials left behind after the process of separating an ore's valuable fraction from the unprofitable fraction are known as tailings in the mining industry. Mixing tailing, cement and water can create a new material called Cemented paste backfill (CPB). Research and solve the problem of predicting the tensile strength of cement paste backfill based on a polynomial model combined with the Monte Carlo Simulation method. Three models were built to evaluate performance. The optimal performance model is then used to predict the tensile strength of cement paste backfill. The results indicate that using the polynomial regression model has a satisfactory result for predicting the tensile strength of cement paste backfill. The best performance of second order polynomial regression model is evaluated by three metrics such as R2=0.958 RMSE=33.211 kPa MAE=29.097 kPa for testing part in predicting the tensile strength of cemented paste backfill. Finally, the influence of Cement/Tailings ratio and Solid content on the tensile strength on tensile strength and importance is also evaluated with aid of the best performance of second order polynomial regression model.
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