%0 Journal Article
%A NING Fang-li
%A WEI Juan
%A YUE Feng-li
%A ZHANG Peng-nan
%T Recognition and Application of Abnormal Sound Via SVM Based on PSO-PF
%D 2019
%R 10.13190/j.jbupt.2018-246
%J Journal of Beijing University of Posts and Telecommunications
%P 58-63
%V 42
%N 3
%X In order to solve the problems of low recognition accuracy and high computation complexity in abnormal sound signals, a particle filter based on particle swarm optimization (PSO-PF) algorithm is proposed to optimize the parameters of support vector machine (SVM). To improve the estimation precision of particle filter, the particle swarm optimization is applied to drive all the particles to the regions in which their likelihoods are high, by updating the velocity and position of particles constantly. And the algorithm can avoid falling into local optimum in SVM parameter optimization. The experimental results show that the new algorithm can achieve higher recognition accuracy and lower computation complexity for abnormal sounds recognition.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2018-246