Abstract：Rockfill parametric inversion is a multi-variable and multi-constraint nonlinear optimization problem. When the finite element analysis is conducted by the simulator of neural network，highly efficient optimizing algorithm is the problem-solving key. A modified particle swarm optimization algorithm，chaotic particle swarm optimization with direction search(CHPSO-DS) algorithm，is provided to solve the complex problem. In the CHPSO-DS algorithm，the particle is initialized with chaos optimization method in its sub-area，which reduces the influence caused by initial position of particle，and then the local search capability of the algorithm is increased by direct search method. For comparison，the CHPSO-DS algorithm and genetic algorithm are used to back analyze parameters of Shuibuya concrete face rockfill dam on the basis of measured displacements. The results show that the CHPSO-DS algorithm can converge quickly and is very robust，and it takes shorter time compared with genetic algorithm in a same precision level. Those show that CHPSO-DS algorithm is very excellent. At last，the calculated mechanical parameters are used to forecast the settlements of the monitoring points of Shuibuya concrete face rockfill dam. Forecasted values are in good agreement with the measured values，which indicates that the CHPSO-DS algorithm can be well applied to the displacement back analysis in geotechnical engineering.
