Title :
Vertical Particle Swarm Optimization Algorithm and its Application in Soft-Sensor Modeling
Author_Institution :
Shanghai DianJi Univ., Shanghai
Abstract :
Vertical particle swarm optimization algorithm (VPSO) is proposed in this paper. The new algorithm assumes that the particles tend to fly towards two directions. One is flying toward the global best particle. The other is flying toward the vertical direction. And there is a random value produced in every iteration step to measure the probability of flying into two directions. Both VPSO and particle swarm optimization algorithm (PSO) are used to train neural network (NN) and applied in soft-sensor of acrylonitrile yield. Finally, simulation results show that the method proposed by this paper is feasible and effective in soft-sensor of acrylonitrile yield.
Keywords :
chemical engineering; chemical sensors; iterative methods; learning (artificial intelligence); particle swarm optimisation; random processes; acrylonitrile yield; iteration process; neural network training; random value; soft-sensor modeling; vertical particle swarm optimization algorithm; Birds; Computational modeling; Convergence; Cybernetics; Machine learning; Machine learning algorithms; Neural networks; Optimization methods; Particle swarm optimization; Stochastic processes; Acrylonitrile; Optimization; Particle swarm optimization algorithm; Soft-sensing;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370472
