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In this paper, a cooperative binary-real particle swarm optimization is applied to tune the structure and parameters of a neural network. A neural network with switches of its links, which is used to decide whether there is a link between two neurons or not, is introduced firstly. Thus, the structure of a neural network can be decided by the switches. A cooperative binary-real particle swarm optimization...
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...
In the ethylene distillation process, ethylene concentration fails to be effectively controlled if lacking theoretical guidance. To a certain extent, the neural network method can estimate and control ethylene concentration, but there are some limitations, such as overfitting and low reliability. In this paper, a hybrid algorithm is proposed for the soft sensing modeling of ethylene distillation column...
This paper proposes an improved PSO (particle swarm optimizer) named as BDPSO (behavior-distance PSO). In BDPSO particle changes fly behaviors guided by the optimum of each particle and the optimum found by the whole particles. In this scheme, individuals can adapt themselves more suitable to search for the destination. Some benchmark functions are tested for comparison the performance between BDPSO...
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