Performance of the ridge regression method as applied to complex linear and nonlinear models

2003 ◽  
Vol 67 (1) ◽  
pp. 69-78 ◽  
Author(s):  
S.H. Ngo ◽  
S. Kemény ◽  
A. Deák
2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Rafael Macedo-Barragán ◽  
Victalina Arredondo-Ruiz ◽  
Carlos Haubi-Segura ◽  
Paola Castillo-Zamora

Author(s):  
German A Munoz-Hernandez ◽  
Ana S Damian-Mora ◽  
Jose Ramirez-Espinoza ◽  
Jesus Chavez-Galan

The applications of electrical energy converters are wide. It is a common device that can be found in almost every apparatus, both industrial and domestic. This work will deal with linear and nonlinear models of DC/DC converters. Those models will used to probe, by simulation, classic and advance controllers. PID controllers have shown a good response regulating DC/DC converters, for that reason the inclusion of two more degree of freedom due to the Integral and derivative of Fractional Order, could improve the performance of these controllers. Furthermore, Piecewise modeling can be useful to obtain adaptive controllers whose parameters change at different operational conditions.


2018 ◽  
Vol 1 (1) ◽  
pp. 197-204
Author(s):  
Tomasz Cepowski

Abstract The article presents the use of multiple regression method to identify added wave resistance. Added wave resistance was expressed in the form of a four-state nominal function of: “thrust”, “zero”, “minor” and “major” resistance values. Three regression models were developed for this purpose: a regression model with linear variables, nonlinear variables and a large number of nonlinear variables. The nonlinear models were developed using the author's algorithm based on heuristic techniques. The three models were compared with a model based on an artificial neural network. This study shows that non-linear equations developed through a multiple linear regression method using the author’s algorithm are relatively accurate, and in some respects, are more effective than artificial neural networks.


1998 ◽  
Vol 22 (1) ◽  
pp. 153-165 ◽  
Author(s):  
Roger P. Woods ◽  
Scott T. Grafton ◽  
John D. G. Watson ◽  
Nancy L. Sicotte ◽  
John C. Mazziotta

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14 ◽  
Author(s):  
Hijaz Ahmad ◽  
Tufail A. Khan ◽  
Predrag S. Stanimirović ◽  
Yu-Ming Chu ◽  
Imtiaz Ahmad

Variational iteration method has been extensively employed to deal with linear and nonlinear differential equations of integer and fractional order. The key property of the technique is its ability and flexibility to investigate linear and nonlinear models conveniently and accurately. The current study presents an improved algorithm to the variational iteration algorithm-II (VIA-II) for the numerical treatment of diffusion as well as convection-diffusion equations. This newly introduced modification is termed as the modified variational iteration algorithm-II (MVIA-II). The convergence of the MVIA-II is studied in the case of solving nonlinear equations. The main advantage of the MVIA-II improvement is an auxiliary parameter which makes sure a fast convergence of the standard VIA-II iteration algorithm. In order to verify the stability, accuracy, and computational speed of the method, the obtained solutions are compared numerically and graphically with the exact ones as well as with the results obtained by the previously proposed compact finite difference method and second kind Chebyshev wavelets. The comparison revealed that the modified version yields accurate results, converges rapidly, and offers better robustness in comparison with other methods used in the literature. Moreover, the basic idea depicted in this study is relied upon the possibility of the MVIA-II being utilized to handle nonlinear differential equations that arise in different fields of physical and biological sciences. A strong motivation for such applications is the fact that any discretization, transformation, or any assumptions are not required for this proposed algorithm in finding appropriate numerical solutions.


2006 ◽  
Vol 3 (2) ◽  
pp. 145-161 ◽  
Author(s):  
S-P Kim ◽  
J C Sanchez ◽  
Y N Rao ◽  
D Erdogmus ◽  
J M Carmena ◽  
...  

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