Feedback identifying seepage parameters of 3D aquifer based on particle swarm optimization and support vector machine

For actual engineering, the aquifers are generally three dimensional anisotropic problems, aiming at the computing time too long and local optimization limitation of conventional method, a new method of three dimensional seepage parameters identification based on support vector machine and particle swarm optimization is proposed. Adopting orthogonal experimental design and finite element program producing training samples, using SVM mapping, the nonlinear relation between water heads and seepage parameters is established. Then taking error objective function as the fitness value of particle swarm optimization, the seepage parameters should be identified by PSO. The method can directly utilize the large scale seepage finite element program. The computing example is given to prove that the method has favorable efficiency and precision.