中南大学学报（自然科学版）2013，Vol.44Issue(4)：1626-1633,8.
RandWPSO-LSSVM反演方法及其在大型地下工程中的应用
RandWPSO-LSSVM inversion method and its application in large-scale underground engineering
摘要
Abstract
The PSO and SVM were improved because of their characteristics and limitations, and the RandWPSO-LSSVM inversion model was established. After the learning and test samples were obtained by orthogonal experimental design, uniform experimental design and three-dimensional finite-element computation, the mechanics parameter of adjoining rock and initial stress field of large-scale surge shaft engineering of Nuozhadu hydro-power station were inversed. The results show that the optimization effect of RandWPSO is better than that of PSO for the LSSVM prediction model. Through inversing, x direction lateral pressure coefficient is 2.641 5 and y direction lateral pressure coefficient is 2.083 1, and the modulus of the fresh rock mass, the upper bed of slightly weathered rock mass, the lower course of slightly weathered rock mass, the strong weathered rock mass and the fault are 24.849 2, 10.898 7, 2.839 8, 0.270 4 and 0.651 3 GPa, respectively. The error between displacement obtained by feedback calculation and displacement obtained by measurement is little, therefore, the parameter obtained by inversion and the RandWPSO-LSSVM inversion model are established reasonably, and the parameter design and stability analysis in construction of large-scale underground engineering could be guided effectively.关键词
随机权重粒子群/最小二乘支持向量机/反演/大型地下洞室/弹性模量/调压井Key words
random weight particle swarm optimization/ least squares support vector machine/ inversion/ large-scale underground cavern/ modulus/ surge shaft分类
建筑与水利引用本文复制引用
聂卫平,徐卫亚,王伟..RandWPSO-LSSVM反演方法及其在大型地下工程中的应用[J].中南大学学报（自然科学版）,2013,44(4):1626-1633,8.基金项目
国家自然科学基金资助项目(51109069) （51109069）
