摘要
///In the course of tomographic static correction of seismic travel-time, the optimization of inversion algorithm has always been technical difficulty. The difference from the conventional linear inversion algorithm is that heuristic colony-forming intellectualized algorithm possesses the following advantages: adaptive, self-studying, intellectualized searching and so on, which has become a high-efficiency overall nonlinear optimization-searching algorithm. The introduction of quantum-behaved particle swarm optimization based on the probability choice mechanism, which can effectively overcome the precocity and improve the overall searching ability. And based on this, the immunization and clone choice mechanism of immunity evolution algorithm are induced into the mapping inversion of seismic tomography to increase antibody’s diversification and further guide the overall searching of the particles. In the end, the quantum-behaved particle swarm optimization with immunity algorithm (IQPSO)is established. Through the test calculation between the theoretical model and the comprehensive static correction data near the earth surface, the effectiveness and practicability of the algorithm are proved.