View source for Issue:Opportunities for application of the intercriteria analysis method to neural network preprocessing procedures

[[Category:Publications on intuitionistic fuzzy sets|{{PAGENAME}}]]
[[Category:Publications in Notes on IFS|{{PAGENAME}}]]
[[Category:Publications in 2015 year|{{PAGENAME}}]]
{{issue/title
 | title           = Opportunities for application of the intercriteria analysis method to neural network preprocessing procedures
 | shortcut        = nifs/21/4/143-152
}}
{{issue/author
 | author          = Sotir Sotirov
 | institution     = Laboratory of Intelligent Systems, University “Prof. Dr. Assen Zlatarov”
 | address         = 1 “Prof. Yakimov” Blvd., Burgas 8010, Bulgaria
 | email-before-at = ssotirov
 | email-after-at  = btu.bg
}}
{{issue/data
 | conference      = 
 | issue           = [[Notes on Intuitionistic Fuzzy Sets/21/4|"Notes on IFS", Volume 21, 2015, Number 4]], pages 143–152
 | file            = NIFS-21-4-143-152.pdf
 | format          = PDF
 | size            = 275
 | abstract        = The artificial neural networks (ANN) are a tool that can be used for object recognition and identification. However, there are certain limits when we may use ANN, and the number of the neurons is one of the major parameters during the implementation of the ANN. On the other hand, the bigger number of neurons slows down the learning process. In our paper, we use a method for removing the number of the neurons without reducing the error between the target value and the real value obtained at the output of the ANN’s output. The method uses the recently proposed approach of InterCriteria Analysis, based on index matrices and intuitionistic fuzzy sets, which aims to detect possible correlations between pairs of criteria. In this paper we use the data from 11 criteria of crude oil measurements.
 | keywords        = Intercriteria analysis, Intuitionistic fuzzy sets, Neural networks, Crude oil.
 | ams             = 03E72.
 | references      = 
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