Multiple Center Intelligent Fault Recognition Strategy Based on Adaptive Mutation Chaos BA
We propose an adaptive mutation algorithm based on chaos to solve the problem of multiple center identification.First-ly,priority is introduced into multiple objective optimization,including recognition accuracy,number of optimization centers and distance relationship.According to the characteristics of various data,the priority is adjusted to ensure the number of adap-tive optimization centers and maintain the original accuracy,and the adaptive mutation chaotic bat algorithm is used for optimi-zation.The simulation results show that the proposed strategy has more extensive recognition ability for different distribution char-acteristics of data,and has good recognition performance for nonlinear separation data.
万方数据
维普
