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Performance Comparison of Various Kernels of Support Vector Regression for Predicting Option Price
International Journal of Discrete Mathematics
Volume 4, Issue 1, June 2019, Pages: 21-31
Received: Feb. 6, 2019; Accepted: Mar. 18, 2019; Published: Apr. 10, 2019
Authors
Arindam Kumar Paul, Department of Mathematics, Khulna University, Khulna, Bangladesh
Raju Roy, Department of Mathematics, Khulna University, Khulna, Bangladesh
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Abstract
The study of the functioning of hepatitis B viruses in the liver cell using methods of mathematical modeling is considered one of the topical issues. In this article, the results on identifying of areas of regimes of the functional-differential equations of the mathematical model of regulatory mechanisms of hepatocyte with hepatitis B viruses (HBV) were presented. Characteristic modes of the regulatory of the interrelated activity of the molecular genetic mechanisms of the liver cells and viruses of hepatitis B are analyzed. The features of the area of the chaotic regime regulatory related activities of molecular genetic mechanisms of the hepatocyte and HBV by analyzing the dynamics of the Lyapunov exponent. Defined small regions with regular behavior - "r-windows" in the field of dynamic chaos. The regulatory of the hepatocyte and HBV can be moved from the region of dynamic chaos to normal region by using "r-windows". The results of the computational experiment on the quantitative analysis of the regulatory of liver cell and HBV are presented.
Keywords
Support Vector Regression, Gaussian Process, Financial Data Modeling and Forecasting, Option Price, Principal Component Analysis
Biplab Madhu, Arindam Kumar Paul, Raju Roy, Performance Comparison of Various Kernels of Support Vector Regression for Predicting Option Price, International Journal of Discrete Mathematics. Vol. 4, No. 1, 2019, pp. 21-31. doi: 10.11648/j.dmath.20190401.14
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