Structure Learning of High-Order Dynamic Bayesian Networks via Particle Swarm Optimization with Order Invariant Encoding

2021 ◽  
pp. 158-171
Author(s):  
David Quesada ◽  
Concha Bielza ◽  
Pedro Larrañaga
2018 ◽  
Vol 16 (1) ◽  
pp. 1022-1036
Author(s):  
Jingyun Wang ◽  
Sanyang Liu

AbstractThe problem of structures learning in Bayesian networks is to discover a directed acyclic graph that in some sense is the best representation of the given database. Score-based learning algorithm is one of the important structure learning methods used to construct the Bayesian networks. These algorithms are implemented by using some heuristic search strategies to maximize the score of each candidate Bayesian network. In this paper, a bi-velocity discrete particle swarm optimization with mutation operator algorithm is proposed to learn Bayesian networks. The mutation strategy in proposed algorithm can efficiently prevent premature convergence and enhance the exploration capability of the population. We test the proposed algorithm on databases sampled from three well-known benchmark networks, and compare with other algorithms. The experimental results demonstrate the superiority of the proposed algorithm in learning Bayesian networks.


2018 ◽  
Vol 7 (4.15) ◽  
pp. 469
Author(s):  
Pakedam Lare ◽  
Byamakesh Nayak ◽  
Srikanta Dash ◽  
Jiban Ballav Sahu

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.  


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