Fuzzy rule-based ensemble with use of linguistic associations mining for time series prediction

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F13%3AA14017T8" target="_blank" >RIV/61988987:17610/13:A14017T8 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—

Result language
angličtina
Original language name
Fuzzy rule-based ensemble with use of linguistic associations mining for time series prediction
Original language description
There are many various methods to forecast time series. However, there is no single forecasting method that generally outperforms any other. Consequently, there always exists a danger of choosing a method that is inappropriate for a given time series. Toovercome such a problem, distinct ensemble techniques are being proposed. These techniques combine more individual forecasting methods. In this contribution, we employ the so called fuzzy rule-based ensemble to determine the weights based on time seriesfeatures such as trend, seasonality or stationarity. For identification of fuzzy rule base, we use linguistic association mining. An exhaustive experimental justification is provided.
Czech name
—
Czech description
—

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 8th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT)
ISBN
9789078677789
ISSN
—
e-ISSN
—
Number of pages
8
Pages from-to
408-415
Publisher name
Atlantis Press
Place of publication
—
Event location
Milano
Event date
Jan 1, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000327668700063

Similar results(10)