Time Series forecasting using machine learning methods

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F09%3A00144532" target="_blank" >RIV/62156489:43110/09:00144532 - isvavai.cz</a>

Alternative codes found

RIV/00216305:26210/09:PU86182

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Time Series forecasting using machine learning methods

Original language description

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.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

IN - Informatics

OECD FORD branch

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Project

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Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2009

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Information Society

ISSN

1581-9973

e-ISSN

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Volume of the periodical

A

Issue of the periodical within the volume

1

Country of publishing house

SI - SLOVENIA

Number of pages

4

Pages from-to

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UT code for WoS article

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EID of the result in the Scopus database

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