University of Limerick
Browse

Forecasting energy time-series data using a fuzzy ARTMAP neural network

Download (509.54 kB)
conference contribution
posted on 2021-08-06, 10:46 authored by Willian de Assis Pedrobon Ferreira, IAN GROUTIAN GROUT, Alexandre César Rodrigues da Silva
Time-series forecasting is an important field of machine learning and is fundamental in analyzing trends based on historical data from various sources. In this paper, a fuzzy ARTMAP neural network for time series forecasting is presented. To validate the proposed system, two energy-related datasets from Great Britain were selected. With a promising processing time and accuracy as good as a traditional machine learning algorithm, the fuzzy ARTMAP neural network has shown that can be a good option to perform forecasting considering different time-based data issues.

History

Publication

2020 International Conference on Power, Energy and Innovations (ICPEI);pp.1-4

Publisher

IEEE Computer Society

Note

peer-reviewed

Other Funding information

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior -Brasil (CAPES)

Rights

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Language

English

Usage metrics

    University of Limerick

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC