Particle Swarm Optimization of the Fuzzy Integrators for Time Series Prediction Using Ensemble of IT2FNN Architectures

2016 ◽  
pp. 141-158 ◽  
Author(s):  
Jesus Soto ◽  
Patricia Melin ◽  
Oscar Castillo
Keyword(s):  
Time Series ◽  
Particle Swarm Optimization ◽  
Time Series Prediction ◽  
Particle Swarm ◽  
Swarm Optimization

Study on Chaotic Time Series Prediction Algorithm for Kent Mapping Based on Particle Swarm Optimization

2014 ◽  
Vol 511-512 ◽  
pp. 941-944 ◽  
Author(s):  
Hong Li Bian
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Particle Swarm Optimization ◽  
Bp Neural Network ◽  
Time Series Prediction ◽  
Particle Swarm ◽  
Chaotic Time Series ◽  
Learning Ability ◽  
Swarm Optimization ◽  
Chaotic Time Series Prediction

Based on the particle swarm optimization (PSO) and BP neural network (BPNN), an algorithm for BP neural network optimized particle swarm optimization (PSOBPNN) is proposed. In the algorithm, PSO is used to obtain better network initial threshold and weight to compensate the defect of connection weight and thresholds of BPNN, thus it can make BPNN have faster convergence and greater learning ability. The efficiency of the proposed prediction method is tested by the simulation of the chaotic time series for Kent mapping. The simulations results show that the proposed method has higher forecasting accuracy compared with the BPNN, so it is proved that the algorithm is feasible and effective in the chaotic time series prediction.

scholarly journals Nonlinear Time Series Prediction Model Based on Particle Swarm Optimization B-spline Network

2018 ◽  
Vol 51 (21) ◽  
pp. 219-223
Author(s):  
Lingshuang Kong ◽  
Xiaolong Gong ◽  
Chuanlai Yuan ◽  
Huiqin Xiao ◽  
Jianhua Liu
Keyword(s):  
Time Series ◽  
Particle Swarm Optimization ◽  
Prediction Model ◽  
Time Series Prediction ◽  
Particle Swarm ◽  
Nonlinear Time Series ◽  
Swarm Optimization ◽  
B Spline ◽  
Model Based
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