PERFORMANCE ANALYSIS OF LSTM MODEL WITH MULTI-STEP AHEAD STRATEGIES FOR A SHORT-TERM TRAFFIC FLOW PREDICTION

Basit Öğe Kaydı
dc.authoridDOGAN, Erdem/0000-0001-7802-641X
dc.contributor.authorDogan, Erdem
dc.date.accessioned2025-01-21T16:43:21Z
dc.date.available2025-01-21T16:43:21Z
dc.date.issued2021
dc.departmentKırıkkale Üniversitesi
dc.description.abstractIn this study, the effect of direct and recursive multi-step forecasting strategies on the short-term traffic flow forecast performance of the Long Short-Term Memory (LSTM) model is investigated. To increase the reliability of the results, analyses are carried out with various traffic flow data sets. In addition, databases are clustered using the k-means++ algorithm to reduce the number of experiments. Analyses are performed for different time periods. Thus, the contribution of strategies to LSTM was examined in detail. The results of the recursive based strategy performances are not satisfactory. However, different versions of the direct strategy performed better at different time periods. This research makes an important contribution to clarifying the compatibility of LSTM and forecasting strategies. Thus, more efficient traffic flow prediction models will be developed and systems such as Intelligent Transportation System (ITS) will work more efficiently. A practical implication for researchers that forecasting strategies should be selected based on time periods.
dc.identifier.doi10.20858/sjsutst.2021.111.2
dc.identifier.endpage31
dc.identifier.issn0209-3324
dc.identifier.issn2450-1549
dc.identifier.scopus2-s2.0-85110738668
dc.identifier.scopusqualityQ3
dc.identifier.startpage15
dc.identifier.urihttps://doi.org/10.20858/sjsutst.2021.111.2
dc.identifier.urihttps://hdl.handle.net/20.500.12587/25251
dc.identifier.volume111
dc.identifier.wosWOS:000669442900002
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherFac Transport Silesian Univ Technology
dc.relation.ispartofScientific Journal of Silesian University of Technology-Series Transport
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241229
dc.subjecttraffic flow; LSTM; short-term prediction; multi-step ahead strategies
dc.titlePERFORMANCE ANALYSIS OF LSTM MODEL WITH MULTI-STEP AHEAD STRATEGIES FOR A SHORT-TERM TRAFFIC FLOW PREDICTION
dc.typeArticle

Dosyalar

Koleksiyon

WOS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu