A novel chemistry based metaheuristic optimization method for mining of classification rules

2012 ◽  
Vol 39 (12) ◽  
pp. 11080-11088 ◽  
Author(s):  
Bilal Alatas
2018 ◽  
Vol 7 (4.15) ◽  
pp. 272 ◽  
Author(s):  
Srikanta Kumar Dash ◽  
Byamakesh Nayak ◽  
Jiban Ballav Sahu ◽  
Rojalin Rout

The harmonic elimination of multilevel inverters is a complicated task that includes nonlinear transcendental equations. With the increase in the level of the multilevel inverter, the no of variables of the equation also increases which makes the problem more complicated. Metaheuristic optimization algorithms play an important role in finding out optimum switching angles required for elimination of harmonics in a lesser computational time avoiding multiple local minima. This paper deals with the harmonic elimination of cascaded multilevel inverter using whale optimization algorithm. The whale optimization method has the ability to escape local minima and it takes less time of computation of results. Results are verified theoretically by taking an example of a 15-level cascaded H-bridge inverter fed from equal d.c.sources. The above scheme well minimizes lower order harmonics and gives better output voltage and a low total harmonic distortion.  


2019 ◽  
Vol 24 (12) ◽  
pp. 8823-8856 ◽  
Author(s):  
Oscar Maciel ◽  
Arturo Valdivia ◽  
Diego Oliva ◽  
Erik Cuevas ◽  
Daniel Zaldívar ◽  
...  

Computers ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 124
Author(s):  
Camilo Andres Arenas-Acuña ◽  
Jonathan Andres Rodriguez-Contreras ◽  
Oscar Danilo Montoya ◽  
Edwin Rivas-Trujillo

The problem of parametric estimation in single-phase transformers is addressed in this research from the point of view of metaheuristic optimization. The parameters of interest are the series resistance and reactance as well as the magnetization resistance and reactance. To obtain these parameters considering only the voltage and the currents measured in the terminals of the transformer, a nonlinear optimization model that deals with the minimization of the mean square error among the measured and calculated voltage and current variables is formulated. The nonlinear programming model is solved through the implementation of a simple but efficient metaheuristic optimization technique known as the black-hole optimizer. Numerical simulations demonstrate that the proposed optimization method allows for the reduction in the estimation error among the measured and calculated variables when compared with methods that are well established in the literature such as particle swarm optimization and genetic algorithms, among others. All the simulations were carried out in the MATLAB programming environment.


IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Siamak Talatahari ◽  
Mahdi Azizi ◽  
Mohamad Tolouei ◽  
Babak Talatahari ◽  
Pooya Sareh

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