基于MMF模型和Richards模型的组合预测模型应用研究
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摘要
路基沉降预测是路基安全性评价的重要依据,由于沉降受多种复杂因素的影响,单一预测模型在预测精度和可靠性方面总受到限制,为充分利用各种模型的优缺点,本文选择MMF模型和Richards模型两种单一预测模型,建立路基沉降的组合预测模型,通过实例分析表明本文建立的组合预测模型的预测值与实测值吻合较好,较单一预测模型精度明显提高,预测精度满足工程要求。
The subgrade settlement prediction is an important basis for subgrade safety evaluation. Since subsidence is affected by many complex factors,the single prediction model is always limited in terms of prediction accuracy and reliability. In order to make full use of the advantages and disadvantages of various models,this paper chooses The MMF model and the Richards model are two kinds of single prediction models. The combined forecasting model of subgrade settlement is established. The example analysis shows that the predicted value of the combined forecasting model established in this paper is in good agreement with the measured value,the accuracy of the single prediction model is obviously improved,and the prediction accuracy is satisfied.
The subgrade settlement prediction is an important basis for subgrade safety evaluation. Since subsidence is affected by many complex factors,the single prediction model is always limited in terms of prediction accuracy and reliability. In order to make full use of the advantages and disadvantages of various models,this paper chooses The MMF model and the Richards model are two kinds of single prediction models. The combined forecasting model of subgrade settlement is established. The example analysis shows that the predicted value of the combined forecasting model established in this paper is in good agreement with the measured value,the accuracy of the single prediction model is obviously improved,and the prediction accuracy is satisfied.
引文
[1]肖治宇,陈昌富.软土路基沉降预测Richards模型方法[J].公路交通科技,2008,25(11):29-32.
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[3]周斌.软土地基沉降特征分析及MMF模型的应用[J].路基工程,2012,(05):177-179.
[4]朱珉仁.Morgan-Mercer-Flodin模型和Weibull模型的拟合[J].数学的实践与认识,2003,33(1):1-4.
[5]朱霄珣,徐搏超.遗传算法对SVR风速预测模型的多参数优化[J].电机与控制学报,2017,21(02):70-75.
[6]余胜威.MATLAB优化算法案例分析与应用[M].北京:清华大学出版社,2015.
[7]陈华友.组合预测方法有效性理论及其应用[M].北京:科学出版社,2008.
[8]谌芳.非负变权组合预测模型在建筑物沉降预测中的应用[J].北京测绘,2018,(04):447-451.
[9]黄文飞,万凯.组合预测模型在矿区沉降预测中的应用[J].北京测绘,2017,(02):41-44.
[10]杨建文,杨德宏.基于Helmert方差分量估计建立沉降分析变权组合模型[J].工程勘察,2014,42(10):73-77.
[11]赵明华,刘煜.软土路基沉降变权重组合S型曲线预测方法研究[J].岩土力学,2005,26(09):1443-1447.
[12]曹文贵,印鹏.基于数据新旧程度和预测取值区间调整的沉降组合预测方法[J].岩土力学,2017,38(02):534-540.
[2]宰金珉,梅国雄.全过程的沉降量预测方法研究[J].岩土力学,2000,21(04):322-325.
[3]周斌.软土地基沉降特征分析及MMF模型的应用[J].路基工程,2012,(05):177-179.
[4]朱珉仁.Morgan-Mercer-Flodin模型和Weibull模型的拟合[J].数学的实践与认识,2003,33(1):1-4.
[5]朱霄珣,徐搏超.遗传算法对SVR风速预测模型的多参数优化[J].电机与控制学报,2017,21(02):70-75.
[6]余胜威.MATLAB优化算法案例分析与应用[M].北京:清华大学出版社,2015.
[7]陈华友.组合预测方法有效性理论及其应用[M].北京:科学出版社,2008.
[8]谌芳.非负变权组合预测模型在建筑物沉降预测中的应用[J].北京测绘,2018,(04):447-451.
[9]黄文飞,万凯.组合预测模型在矿区沉降预测中的应用[J].北京测绘,2017,(02):41-44.
[10]杨建文,杨德宏.基于Helmert方差分量估计建立沉降分析变权组合模型[J].工程勘察,2014,42(10):73-77.
[11]赵明华,刘煜.软土路基沉降变权重组合S型曲线预测方法研究[J].岩土力学,2005,26(09):1443-1447.
[12]曹文贵,印鹏.基于数据新旧程度和预测取值区间调整的沉降组合预测方法[J].岩土力学,2017,38(02):534-540.