Title :
A new particle swarm optimization and the application in the soft sensor modeling
Author :
Dang, Mingmei ; Wang, Zhenlei ; Qian, Feng
Author_Institution :
East China Univ. of Sci. & Technol., Shanghai, China
Abstract :
Aiming at the disadvantages of the standard Particle Swarm Optimization (PSO), a new particle swarm optimization algorithm based on dual mutation(DDPSO) is proposed. By comparing and analyzing the results of several Benchmark functions, the excellent performance of PSO is proved. The improved PSO is applied to optimize the structure and parameters in artificial neural network(ANN). The availability of algorithm optimizing neural network is proved by applying ANN in soft sensor modeling of propylene concentration measurement.
Keywords :
chemical sensors; chemical variables measurement; computerised instrumentation; neural nets; particle swarm optimisation; ANN; DDPSO; algorithm optimizing neural network; artificial neural network; benchmark function; dual mutation; particle swarm optimization; propylene concentration measurement; soft sensor modeling; Ant colony optimization; Artificial neural networks; Automatic control; Chemical processes; Chemical technology; Clustering algorithms; Convergence; Educational technology; Particle swarm optimization; Particle tracking; dual mutation; modeling; neural network; particle swarm optimization; soft sensor;
Conference_Titel :
Control and Automation (ICCA), 2010 8th IEEE International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-5195-1
Electronic_ISBN :
1948-3449
DOI :
10.1109/ICCA.2010.5524322
