| 基于?－SVR和GA的初始地应力场位移反分析方法研究 |
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| 引用本文： | 余志雄,周创兵,陈益峰,李俊平.基于?－SVR和GA的初始地应力场位移反分析方法研究[J].岩土力学,2007,28(1):151-156. |
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| 作者姓名： | 余志雄 周创兵 陈益峰 李俊平 |
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| 作者单位： | 1.武汉大学 水资源与水电工程科学国家重点实验室，武汉 430072；2.广州市广园路建设公司，广州 510010； 3.鸡西大学，黑龙江 鸡西 158100 |
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| 摘 要： | 基于一种改进的支持向量机（?－SVR）和改进的遗传算法（GA），提出一种初始地应力场位移反分析方法。该方法通过正交设计方法安排较少次数的正分析方案，用?－SVR对正分析中测点位移值与参数构成的样本集进行学习，建立参数取值与观测点测值的非线性隐式方程；采用确定性或随机反分析的思路确定反分析的优化目标函数，并利用GA搜索最优参数取值。采用?－SVR方法建立的参数取值与位移量测点测值的非线性隐式方程，能够以很高的精度拟合和预测不同参数取值时的观测点测值，因此，可以用该隐式方程代替正分析，减少计算量；采用改进的GA方法能够准确搜索到最优参数；搜索到的最优参数值与理论值相当吻合。算例表明，基于?－SVR和GA的初始地应力场位移反分析方法是一种行之有效的初始地应力场位移反分析方法，可以广泛用于初始地应力场确定性反分析和随机反分析。
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| 关 键 词： | 支持向量机 改进遗传算法 初始地应力场 反分析 正交设计 ?－SVR |
| 收稿时间： | 2005-04-11 |
Study on ?－SVR and modified GA in back analysis of initial stress fields from displacements |
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| YU Zhi-xiong,ZHOU Chuang-bing,CHEN Yi-feng,LI Jun-ping.Study on ?－SVR and modified GA in back analysis of initial stress fields from displacements[J].Rock and Soil Mechanics,2007,28(1):151-156. |
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| Authors: | YU Zhi-xiong ZHOU Chuang-bing CHEN Yi-feng LI Jun-ping |
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| Institution: | 1.State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China; 2. Guangzhou Guangyuan Construction Company, Guangzhou 510010, China; 3. Jixi University, Jixi 158100, China |
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| Abstract: | A method of back analysis of initial stress fields from displacement is presented based on a kind of modified support vector machine named ?-SVR and a kind of modified genetic algorithms. By using orthogonal experiment method, only several positive analysis are done. ?-SVR used the measuring points’ displacement and parameters of positive analysis as samples to build the nonlinear implicit equations between them. Then modified genetic algorithms are used to find the optimal parameters on deterministic or stochastic optimal object function. The equations built by ?-SVR can fit and forecast the measuring points’ displacements under different parameters with high precision. So these equations can substitute positive analysis, and the amount of computation will reduce greatly. With modified genetic algorithms, the optimal parameters can be found accurately. Example shows the method presented is an effective back analysis method for initial stress fields from displacements. It can be widely used in deterministic or stochastic back analysis of initial stress fields from displacements. |
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| Keywords: | support vector machine(SVM) modified genetic algorithms initial stress fields back analysis orthogonal experiment ?－SVR stochastic back analysis |
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