Application of the Intuitionistic Fuzzy InterCriteria Analysis Method to a Neural Network Preprocessing Procedure
Authors
Sotir Sotirov, Vassia Atanassova, Evdokia Sotirova, Veselina Bureva, Deyan Mavrov
Corresponding Author
Sotir Sotirov
Available Online June 2015.
- DOI
- 10.2991/ifsa-eusflat-15.2015.222How to use a DOI?
- Keywords
- Neural network, InterCriteria Analysis, Intuitionistic fuzziness.
- 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 propose a method for removing the number of the neurons without reducing the error between the target value and the real value obtained on the output of the ANN’s exit. 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.
- Copyright
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Sotir Sotirov AU - Vassia Atanassova AU - Evdokia Sotirova AU - Veselina Bureva AU - Deyan Mavrov PY - 2015/06 DA - 2015/06 TI - Application of the Intuitionistic Fuzzy InterCriteria Analysis Method to a Neural Network Preprocessing Procedure BT - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology PB - Atlantis Press SP - 1559 EP - 1564 SN - 1951-6851 UR - https://doi.org/10.2991/ifsa-eusflat-15.2015.222 DO - 10.2991/ifsa-eusflat-15.2015.222 ID - Sotirov2015/06 ER -