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GeoLSTM: A road geometry-aware neural network model for spatio-temporal highway traffic speed and intensity forecasting.

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Title: GeoLSTM: A road geometry-aware neural network model for spatio-temporal highway traffic speed and intensity forecasting.
Authors: Franco-Panadés, Gerard1,2,3,4, gerard.franco@upc.edu, Llatje, Òscar4, Giralt, Laia Pagès1,2,3, Jofre-Roca, Luis1,2,3
Source: Expert Systems with Applications; Apr2026, Vol. 305, pN.PAG-N.PAG, 1p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 191525993
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=191525993
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.eswa.2025.130887
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      – Code: eng
        Text: English
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        PageCount: 1
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      – TitleFull: GeoLSTM: A road geometry-aware neural network model for spatio-temporal highway traffic speed and intensity forecasting.
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            NameFull: Franco-Panadés, Gerard
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            NameFull: Llatje, Òscar
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            NameFull: Giralt, Laia Pagès
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            – D: 05
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              Text: Apr2026
              Type: published
              Y: 2026
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              Value: 305
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            – TitleFull: Expert Systems with Applications
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