Pattern Classification on Complex System Using Modified Gustafson- Kessel Algorithm

DOI

10.2991/eusflat-19.2019.99How to use a DOI?

Keywords

Fuzzy c- Means Algorithm Gustafson- Kessel Algorithm Stock Classification Pattern Recognition

Abstract

This work has been focused in the application of Gustafson- Kessel Algorithm in a complex system through a methodology proposed. The complex system here considered will be the financial market. So, the main objective of this paper is to classify objects in two patterns: winner and loser. The methodology is based on application of a method of clustering called Modified Gustafson-Kessel (MGK) in some open companies of the transportation sector and energy sector. Results shows that the use of MGK can better separate the promising actions from the non-promising ones with more precision due to its covariance matrix that can be change for generate the best separability among clusters. This produces a new tool for analysis of the dynamic of stock market with the main aim of given support to investor in make decision.

Copyright

© 2019, 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/).

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TY  - CONF
AU  - Miguel Khatounian Filho
AU  - Leo Koki
AU  - Renato Aguiar
PY  - 2019/08
DA  - 2019/08
TI  - Pattern Classification on Complex System Using Modified Gustafson- Kessel Algorithm
BT  - Proceedings of the 11th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2019)
PB  - Atlantis Press
SP  - 714
EP  - 720
SN  - 2589-6644
UR  - https://doi.org/10.2991/eusflat-19.2019.99
DO  - 10.2991/eusflat-19.2019.99
ID  - Filho2019/08
ER  -