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乔思宇,杨泽发,李志伟,等. 基于AIC准则的煤矿区单点动态沉降时间函数优化选取[J]. 煤炭科学技术,2023,51(6):177−186

. DOI: 10.13199/j.cnki.cst.2022-0047
引用本文:

乔思宇,杨泽发,李志伟,等. 基于AIC准则的煤矿区单点动态沉降时间函数优化选取[J]. 煤炭科学技术,2023,51(6):177−186

. DOI: 10.13199/j.cnki.cst.2022-0047

QIAO Siyu,YANG Zefa,LI Zhiwei,et al. Optimal selection of time functions for describing coal mining-induced dynamic subsidence at single surface point using AIC criterion[J]. Coal Science and Technology,2023,51(6):177−186

. DOI: 10.13199/j.cnki.cst.2022-0047
Citation:

QIAO Siyu,YANG Zefa,LI Zhiwei,et al. Optimal selection of time functions for describing coal mining-induced dynamic subsidence at single surface point using AIC criterion[J]. Coal Science and Technology,2023,51(6):177−186

. DOI: 10.13199/j.cnki.cst.2022-0047

基于AIC准则的煤矿区单点动态沉降时间函数优化选取

Optimal selection of time functions for describing coal mining-induced dynamic subsidence at single surface point using AIC criterion

  • 摘要: 时间函数法是最常用的煤矿区地表动态形变预测方法之一。其中,描述地表单点“S”型沉降过程的数学模型选取直接影响时间函数法的形变预测精度和可靠性。现有研究大都以拟合残差最小化为目标,通过修正或引入“S”型增长数学模型提高时间函数法的预测精度。然而,该方式容易导致“过拟合”现象,增加模型复杂度和参数反演难度。为克服该问题,引入了拟合残差和模型复杂度2个关键的优化选取指标,以来自7个不同地质采矿条件矿区的103个观测点时序沉降值为样本,采用理论分析与赤池信息量准则探讨了12种常见“S”型增长模型在煤矿区地表单点沉降过程描述中的优化选取。结果表明:①12种模型中,5个四参数模型的平均拟合残差为3.51 cm,明显优于二参数Knothe模型(14.10 cm),但仅略优于6个三参数模型(4.78 cm);②在兼顾拟合残差和模型复杂度的准则下,三参数模型普遍优于四参数和二参数,说明三参数模型比较适合描述矿区地表单点动态沉降过程,而四参数和二参数模型则分别存在“过拟合”(过度参数化)和“欠拟合”现象;③在6个三参数模型中,模型的优化选取与覆岩岩性有关。其中,软和中硬覆岩条件下,目前尚未被引入时间函数法的三参数Hossfeld模型能够较好地兼顾拟合残差小和模型复杂度低2个关键指标,但在坚硬覆岩条件下,Weibull模型表现则优于Hossfeld模型。

     

    Abstract: The time function method is one of the most commonly used methods for predicting surface dynamic displacements in coal mine areas. In which, the accuracy and reliability of the predicted displacements, to a large extent, depends on the selected mathematical functions for describing the “S”-typed dynamic subsidence at a single surface point (referred to as time functions). Nearly all of the existing studies primarily improve or introduce “S”-shaped growth functions with a single object to minimizing the fitting residuals between thein-situmonitored and the model-fitted subsidence. Such a strategy, however, would result in “overfitting” (or over-parameterization), thereby increasing the complexity of the constructed time function model and the difficulty of model parameter inversion. To this end, the optimal selection of time functions was analyzed in this paper using two indicators of fitting residual and model complexity, rather than the former one in existing studies. More specifically, time-series subsidence observations at 103 field points in seven coal mining areas with different geological mining conditions were selected to be observation samples for ensuring the applicability of the optimal time function. Then, 12 common “S-shaped” growth models were chosen to candidates, and the theoretical analysis and Akaike information criterion (AIC) were further used to analyze the optimal selection of time function from the chosen 12 “S”-shaped models. The results show that: ① Among the 12 selected models, the mean mis-fitting error of the five four-parameter models is about 3.51 cm, which is obviously smaller than that of the two-parameter Knothe model (14.10 cm), but just slightly smaller than the six three-parameter models (4.78 cm); ② In the view of making a trade-off between fitting residuals and model complexity (assessing by the AIC), the AICs of the six three-parameter models are smaller than those of the four-parameter and two-parameter models.This indicates that the three-parameters models are preferrable to describe the temporal evolution of subsidence at a single point, and the four-parameter and two-parameters models may be over-fitted and under-fitted, respectively; ③ Among the six selected models, the optimal selection of time function is related to the lithology of the overburden rock strata; that is, Hossfeld model, which has not been introduced into the time function method, is preferrable under soft and medium-hard overburden strata, whereas Weibull model is preferrable under hard overburden strata.

     

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