Detail publikace

Time Series forecasting using machine learning methods

ŠTENCL, M. POPELKA, O. ŠŤASTNÝ, J.

Anglický název

Time Series forecasting using machine learning methods

Typ

Článek recenzovaný mimo WoS a Scopus

Jazyk

en

Originální abstrakt

In this paper we concentrate on prediction of future values based on the past course of that variable, traditionally these are solved using statistical analysis – first a time-series model is constructed and then statistical prediction algorithms are applied to it in order to obtain future values. This paper describes Radial Basis Functions (RBF) Neural Network and Two-level Grammatical Evolution. Both these methods are applied to solve prediction of simplified numerical time series. Sample dataset includes forty generated observations and the goal is to predict five future values.

Klíčová slova anglicky

Genetic Algorithm, Prediction of Time Series, RBF Neural Network

Vydáno

2009-10-01

ISSN

1581-9973

Ročník

2009

Číslo

A/1

Strany od–do

66–69

Počet stran

4

BIBTEX


@article{BUT47303,
  author="Michael {Štencl} and Ondřej {Popelka} and Jiří {Šťastný}",
  title="Time Series forecasting using machine learning methods",
  journal="Information Society",
  year="2009",
  volume="2009",
  number="A/1",
  pages="66--69",
  issn="1581-9973"
}