scholarly journals Forecasting Based on High-Order Fuzzy-Fluctuation Trends and Particle Swarm Optimization Machine Learning

Symmetry ◽  
2017 ◽  
Vol 9 (7) ◽  
pp. 124 ◽  
Author(s):  
Jingyuan Jia ◽  
Aiwu Zhao ◽  
Shuang Guan
Keyword(s):  
Machine Learning ◽  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
High Order ◽  
Swarm Optimization

scholarly journals Adaptive Phase-Shifted PWM based on Particle Swarm Optimization for Cascaded H-Bridge Inverter with Unequal Dc-link Voltages

2018 ◽  
Vol 7 (4.15) ◽  
pp. 469
Author(s):  
Pakedam Lare ◽  
Byamakesh Nayak ◽  
Srikanta Dash ◽  
Jiban Ballav Sahu
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Industrial Applications ◽  
High Order ◽  
Control Technique ◽  
Voltage Source ◽  
Switching Frequency ◽  
Swarm Optimization ◽  
The Cost

The cascaded H-Bridge Multilevel Inverter has been found a promising technology in industrial applications because of its higher voltage with less distortion production. Various PWMs techniques have been proposed to push the harmonics frequencies higher than the switching frequency and thus reduces the THD as compared to non-carrier control technique based upon grid frequency. The Phase-Shifted PWM technique has an advantage over others PWM techniques because its harmonics orders are multiples of switching frequency and also depend on the number of levels of the inverter. The phase shifting angle is uniform when the equal voltage sources are adopted. However, in applications where sets of different voltage source levels feed the H-Bridge cells, the Phase Shifted PWM suffers its high order harmonics elimination capability. As a solution to alleviate this problem, an adaptive variable angle approach is proposed in this paper using Particle Swarm Optimization (PSO) algorithm to eliminate desired higher order harmonics. The algorithm is used to minimize the cost function based on high order sideband harmonics elimination equations. The results through MATLAB/Simulink environment shown in this paper confirm the reduction of sideband harmonics of higher orders, and the overall THD.  

Rainfall-runoff modelling using improved machine learning methods: Harris hawks optimizer vs. particle swarm optimization

2020 ◽  
Vol 589 ◽  
pp. 125133 ◽  
Author(s):  
Yazid Tikhamarine ◽  
Doudja Souag-Gamane ◽  
Ali Najah Ahmed ◽  
Saad Sh. Sammen ◽  
Ozgur Kisi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Rainfall Runoff ◽  
Learning Methods ◽  
Swarm Optimization ◽  
Machine Learning Methods
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