IVDF模型在土石坝监测数据预测中的应用
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摘要
土石坝的监测数据预测对于揭示坝体变形规律、保障坝体结构安全具有重要意义。基于分形理论,将改进变维分形模型(IVDF模型)应用于土石坝小数据量监测数据的预测,以铜山源土石坝为例,选取混凝土防渗墙的应变监测数据作为研究对象,对应变进行预测,并分别用灰色模型GM(1,1)和BP神经网络进行对比预测。计算结果证明,IVDF模型充分利用分形的自相似性特征,抗噪性强,预测精度高,适用于小数据量监测数据的预测,具有良好的应用前景。
Forecast of earth-rock Dam's monitoring data is very important in revealing the deformation law of dam as well as in the protection of its structural safety.Based on fractal theory,this paper take Tongshanyuan earth-rock dam as example and attempts to apply the Improved Variable Dimension Fractal Model(IVDF model) in the deformation forecast of earth-rock dam by small amount of monitoring data.The monitored strain data of concrete cut-off wall of Tongshanyuan earth-rock dam is selected as research object to forecast the wall strain the forecast result are compared with the results of gray model GM(1,1) and BP neural network.The results show that,as IVDF Model makes good use of the self-similarity of fractal theory,thus it has advantages of high forecast precision and noise immunity,suit for the forecast with small amount of monitored data and has a promising application prospect.
Forecast of earth-rock Dam's monitoring data is very important in revealing the deformation law of dam as well as in the protection of its structural safety.Based on fractal theory,this paper take Tongshanyuan earth-rock dam as example and attempts to apply the Improved Variable Dimension Fractal Model(IVDF model) in the deformation forecast of earth-rock dam by small amount of monitoring data.The monitored strain data of concrete cut-off wall of Tongshanyuan earth-rock dam is selected as research object to forecast the wall strain the forecast result are compared with the results of gray model GM(1,1) and BP neural network.The results show that,as IVDF Model makes good use of the self-similarity of fractal theory,thus it has advantages of high forecast precision and noise immunity,suit for the forecast with small amount of monitored data and has a promising application prospect.
引文
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[2]张丙印,袁会娜,李全明.基于神经网络和演化算法的土石坝位移反演分析[J].岩石力学,2005,26(4):547-552.
[3]金菊良,杨晓华,金保明,等.遗传算法在均质土坝渗流计算中的应用[J].长江科学院院报,2001,18(1):38-40.
[4]Mandelbrot B B.Les objets fractals:forme,hasard et dimension[M].In:Flammarion,Paris.1975.
[5]李信富,李小凡,武晔.分形理论在地震学中的应用研究[J].地球物理学进展,2007,4(2):411-417.
[6]厉大业,阮炯.分形Hurst指数在彩虹期权定价中的应用[J].复旦大学学报(自然科学版),2007,46(2):156-167.
[7]宋春林,冯端,刘富强,等.变步长和变阈值的分形小波图像压缩算法[J].计算机工程,2007,(14):174-176.
[8]赖道平,吴中如,周红.分形学在大坝安全监测资料分析中的应用[J].水利学报,2004,35(1):100-104.
[9]Mandelbrot B B.The Fractal Geometry of Nature[M].San Francisco:Freeman,1982.
[10]付昱华.变换形成的分形与海洋环境数据分析预测[J].海洋通报,2000,19(1):79-88.
[11]魏海云,许小杰,刘正国,等.浙江省衢州市铜山源水库除险加固工程蓄水安全鉴定监测工程自检报告[R].杭州:浙江广川工程咨询有限公司,2008.
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