Open Access
ARTICLE
Numerical Solution of Linear Regression Based on Z-Numbers by Improved Neural Network
Somayeh Ezadia, Tofigh Allahviranloob
a Department of Applied Mathematics, Hamedan Branch, Islamic Azad University, Hamedan, Iran;
b Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran
* Corresponding Author: Tofigh Allahviranloo,
Intelligent Automation & Soft Computing 2018, 24(1), 193-204. https://doi.org/10.1080/10798587.2017.1328812
Abstract
In this article, the researcher at first focuses on introducing a linear regression based on the Z-number.
In this regression, observations are real, but the coefficients and results of observations are unknown
and in the form of Z-rating. Therefore, to estimate this type of regression, we have three distinct ways
depending on different conditions dominating the problem. The three methods are a combination of
artificial neural networks and fuzzy generalized improvements of the technique. Moreover the method
of calculating the weights of the Z-number neural network has been mentioned and the stability of
neural network weights is considered. In some examples, the answer is estimated compared with the
original answer.
Keywords
Cite This Article
. Somayeh Ezadi and . Tofigh Allahviranloo, "Numerical solution of linear regression based on z-numbers by improved neural network,"
Intelligent Automation & Soft Computing, vol. 24, no.1, pp. 193–204, 2018. https://doi.org/10.1080/10798587.2017.1328812