Novel Particle Swarm Optimization and Its Application in Calibrating the Underwater Transponder Coordinates

作者：Yan, Zheping; Deng, Chao^*; Li, Benyin; Zhou, Jiajia

来源：Mathematical Problems in Engineering, 2014, 2014: UNSP 672412.

DOI：10.1155/2014/672412

• Bench-mark problems
• Improved particle swarm algorithms
• ITS applications
• Particle swarm algorithm
• Searching performance
• Standard optimization
• Time-varying acceleration coefficients
• Underwater transponders

A novel improved particle swarm algorithm named competition particle swarm optimization (CPSO) is proposed to calibrate the Underwater Transponder coordinates. To improve the performance of the algorithm, TVAC algorithm is introduced into CPSO to present an extension competition particle swarm optimization (ECPSO). The proposed method is tested with a set of 10 standard optimization benchmark problems and the results are compared with those obtained through existing PSO algorithms, basic particle swarm optimization (BPSO), linear decreasing inertia weight particle swarm optimization (LWPSO), exponential inertia weight particle swarm optimization (EPSO), and time-varying acceleration coefficient (TVAC). The results demonstrate that CPSO and ECPSO manifest faster searching speed, accuracy, and stability. The searching performance for multimodulus function of ECPSO is superior to CPSO. At last, calibration of the underwater transponder coordinates is present using particle swarm algorithm, and novel improved particle swarm algorithm shows better performance than other algorithms.

• 出版日期2014
• 单位哈尔滨工程大学