Automatic Generation of a Type-2 Fuzzy System for Time Series Forecast based on Genetic Programming

DOI

10.2991/eusflat-19.2019.54How to use a DOI?

Keywords

Fuzzy System Mamdani Genetic Programming Forecasting Noisy Data.

Abstract

This work describes the development of a type 2 Fuzzy Inference System by using Genetic Programming for applications in time series forecasting. The resulting model, called GPFIS-Forecast+ is based on the GPFIS-Forecast created previously, which made use of Multigene Genetic Programming an provided good results. Results show that the system with type 2 fuzzy sets improves the performance, especially for noisy data.

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  - Marco Antonio Cunha Ferreira
AU  - Ricardo Tanscheit
AU  - Marley Vellasco
PY  - 2019/08
DA  - 2019/08
TI  - Automatic Generation of a Type-2 Fuzzy System for Time Series Forecast based on Genetic Programming
BT  - Proceedings of the 11th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2019)
PB  - Atlantis Press
SP  - 385
EP  - 391
SN  - 2589-6644
UR  - https://doi.org/10.2991/eusflat-19.2019.54
DO  - 10.2991/eusflat-19.2019.54
ID  - CunhaFerreira2019/08
ER  -