@Article{10798587.2017.1328812,
AUTHOR = {SomyehÂ Ezdi, TofighÂ Allhvirnloo},
TITLE = {Numerical Solution of Linear Regression Based on Z-Numbers by Improved Neural Network},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {24},
YEAR = {2018},
NUMBER = {1},
PAGES = {193--204},
URL = {http://www.techscience.com/iasc/v24n1/39744},
ISSN = {2326-005X},
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.},
DOI = {10.1080/10798587.2017.1328812}
}