The improved quantum genetic algorithm with its application in fault diagnosis

Abstract

Abstract In this paper, by analyzing the characteristics of the simulated annealing algorithm (SA) and the real double-chain coding target gradient quantum genetic algorithm (DCQGA), the real double-chain coding target gradient quantum genetic simulated annealing algorithm (DCQGSAA) is proposed. Because the performance of LSSVR is extraordinarily sensitive to its key parameters, the proposed algorithm is used to optimize these parameters, then a hybrid non-parametric prediction model is put forward. This model is used in fault prediction of liquid rocket engine thrust. The simulation results show that the proposed model is effective for small samples and multi-dimensional fault prediction.