基于变步长FOA—Richards模型的地表沉降动态预计
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摘要
针对地表动态沉降的非线性和随机性特征,且沉降大致呈现"S"形曲线发展,最终趋向于稳定状态,采用Richards函数进行动态预计。基于采动区地表下沉Richards模型求取参数较为复杂,引入变步长果蝇优化算法(FOA)思想,建立采动区地表下沉动态预计的变步长FOA—Richards模型,以提高预测精度。工程实例分析表明,变步长FOA—Richards模型符合理想的时间函数特征,能够较好地预计出动态下沉值及下沉速度,且精度可靠性较高。
Aiming at nonlinear and random characteristics of the surface dynamic subsidence,the subsidence shows the development of the "S"curve,which eventually tends to be stable.It can be predicted dynamically by the Richards function.Based on the mining area surface sinking Richards model to obtain more complex parameters,the variable step size fruit fly optimization algorithm(FOA)is introduced,and the variable step size FOA-Richards model of the surface subsidence dynamics in the mining area is established to improve prediction accuracy.A case study is given.The result shows that:the variable step size FOA-Richards model can satisy the requirements of perfect time function and can predict the dynamic subsidence value and sinking speed better,thus the accuracy and reliability getting higher.
Aiming at nonlinear and random characteristics of the surface dynamic subsidence,the subsidence shows the development of the "S"curve,which eventually tends to be stable.It can be predicted dynamically by the Richards function.Based on the mining area surface sinking Richards model to obtain more complex parameters,the variable step size fruit fly optimization algorithm(FOA)is introduced,and the variable step size FOA-Richards model of the surface subsidence dynamics in the mining area is established to improve prediction accuracy.A case study is given.The result shows that:the variable step size FOA-Richards model can satisy the requirements of perfect time function and can predict the dynamic subsidence value and sinking speed better,thus the accuracy and reliability getting higher.
引文
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[15]王钧.基于变步长果蝇优化算法的Richards模型参数估计[J].计算机工程与设计,2017,38(9):2402-2406.
[2]朱广轶,沈红霞,王立国.地表动态移动变形预测函数研究[J].岩石力学与工程学报,2011(9):1889-1895.
[3]王正帅,邓喀中.采动区地表动态沉降预测的Richards模型[J].岩土力学,2011,32(6):1664-1668.
[4]KOYA P R,GOSHU A T.Generalized Mathematical Model for Biological Growths[J].Open Journal of Modeling and Simulation,2013,1(4):42-53.
[5]赵亚红,贺黎明,王金星,等.马尔科夫链优化Richards曲线的沉降预测模型[J].测绘通报,2018(6):118-121.
[6]刘玉成,曹树刚,刘延保.可描述地表沉陷动态过程的时间函数模型探讨[J].岩土力学,2010,31(3):925-931.
[7]王军保,刘新荣,刘小军.开采沉陷动态预测模型[J].煤炭学报,2015(3):516-521.
[8]李德海,许国胜,余华中.厚松散层煤层开采地表动态移动变形特征研究[J].煤炭科学技术,2014(7):103-106.
[9]国家煤炭工业局.建筑物、水体、铁路及主要井巷煤柱留设与压煤开采规程[M].北京:煤炭工业出版社,2000.
[10]邢黎峰,孙明高,王元军.生物生长的Richards模型[J].生物数学学报,1998,13(3):348-353.
[11]严超.基于GA-SVM的主要影响角正切求取方法研究[J].黑龙江工程学院学报,2016,30(6):16-19.
[12]王磊.山区地表移动预计修正模型及其参数求取方法[J].煤炭学报,2014,39(6):1070-1076.
[13]张劲满,徐良骥,张坤,等.基于蛙跳PSO-Richards模型的地表沉降动态预计[J].煤炭技术,2018,37(10):91-93.
[14]燕振刚,胡贺年,李广.基于粒子群优化算法的Richards模型参数估计和算法有效性[J].计算机应用,2014,34(10):2827-2830.
[15]王钧.基于变步长果蝇优化算法的Richards模型参数估计[J].计算机工程与设计,2017,38(9):2402-2406.