A dynamic organizational adjustment particle swarm optimization-based particle filter algorithm (OAPSO-PF) is presented in this paper in order to solve the problem of low precision and complicated calculation of particle filter based on particle swarm optimization algorithm(PSO-PF). Through the mutual competition and collaboration among organizations, this algorithm allows the particles to adapt to the environment better and thus reach the goal of global optimization, accordingly enhancing the quality of particles and avoiding particle degradation by the adoption of optimal particle retention. Finally different models are used for simulation experiment and the results indicate that this new algorithm improves the operation speed and precision, it is applicable to practical engineering.
Chen, Zhimin; Bo, Yuming; Wu, Panlong; and Zhou, Weijun
"A new particle filter based on organizational adjustment particle swarm optimization,"
Applied Mathematics & Information Sciences: Vol. 07:
1, Article 22.
Available at: https://digitalcommons.aaru.edu.jo/amis/vol07/iss1/22