Adaptive inversion analysis of material parameters of rock-fill dam based on QGA-MMRVM

被引：0

作者：

Ma Chun-hui ^{[1
,2
]}

Yang Jie ^{[1
,2
]}

Cheng Lin ^{[1
,2
]}

Li Ting ^{[3
]}

Li Ya-qi ^{[1
,2
]}

机构：

[1] Xian Univ Technol, Inst Water Resources & Hydroelect Engn, Xian 710048, Shaanxi, Peoples R China

[2] China Xian Univ Technol, State Key Lab Ecohydraul Northwest Arid Reg China, Xian 710048, Shaanxi, Peoples R China

[3] Nanjing Hydraul Res Inst, Ctr Ecoenvironm, Nanjing 210029, Jiangsu, Peoples R China

来源：

ROCK AND SOIL MECHANICS | 2019年 / 40卷 / 06期

基金：

中国国家自然科学基金;

关键词：

rock-fill dam; parameter inversion analysis; multi-output mixed kernel relevance vector machine; quantum genetic algorithm; adaptivity; RHEOLOGICAL PARAMETERS; VECTOR; PREDICTION;

D O I：

10.16285/j.rsm.2018.0320

中图分类号：

P5 [地质学];

学科分类号：

0709 ; 081803 ;

摘要：

In order to improve the accuracy and applicability of inversion analysis model of material parameters for rockfill dam, an adaptive model based on quantum genetic algorithm (QGA) and multi-output mixed kernel relevance vector machine (MMRVM) is established. By introducing mixed kernel function, the MMRVM can accurately simulate the nonlinear relationship between the material parameters and the settlement of rockfill dam. Therefore, the finite element method (FEM) can be replaced by the MMRVM to reduce time consumption. Then, the kernel parameters of the MMRVM is optimized by the QGA, thus the QGA-MMRVM is adaptable to different inversion analysis problems. The parameters of constitutive model of dam materials can be inverted by fully utilizing QGA's global searching ability. Finally, the influences of the signal-noise ratio and the number of measured points on the calculation result are analyzed. The examples of Gongboxia dam show that the parameters of constitutive model of material can quickly and accurately calculated by the QGA-MMRVM. With its adaptability, the QGA-MMRVM has good application prospect and popularization value in practical engineering.

引用

页码：2397 / 2406

页数：10

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