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Comparative Analysis of Deep Learning Approaches for Predicting EV Charging Station Loads: Spatial, Temporal, and Spatiotemporal Perspectives.

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Main Author: Khor, Gee Pei
Format: Final Year Project
Published: 2024
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://utpedia.utp.edu.my/id/eprint/28676/
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id oai:utpedia.utp.edu.my:28676
record_format eprints
spelling oai:utpedia.utp.edu.my:286762024-08-08T09:34:40Z http://utpedia.utp.edu.my/id/eprint/28676/ Comparative Analysis of Deep Learning Approaches for Predicting EV Charging Station Loads: Spatial, Temporal, and Spatiotemporal Perspectives. Khor, Gee Pei TK Electrical engineering. Electronics Nuclear engineering 2024-05 Final Year Project NonPeerReviewed Khor, Gee Pei (2024) Comparative Analysis of Deep Learning Approaches for Predicting EV Charging Station Loads: Spatial, Temporal, and Spatiotemporal Perspectives. [Final Year Project] (Submitted)
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Khor, Gee Pei
Comparative Analysis of Deep Learning Approaches for Predicting EV Charging Station Loads: Spatial, Temporal, and Spatiotemporal Perspectives.
format Final Year Project
author Khor, Gee Pei
author_facet Khor, Gee Pei
author_sort Khor, Gee Pei
title Comparative Analysis of Deep Learning Approaches for Predicting EV Charging Station Loads: Spatial, Temporal, and Spatiotemporal Perspectives.
title_short Comparative Analysis of Deep Learning Approaches for Predicting EV Charging Station Loads: Spatial, Temporal, and Spatiotemporal Perspectives.
title_full Comparative Analysis of Deep Learning Approaches for Predicting EV Charging Station Loads: Spatial, Temporal, and Spatiotemporal Perspectives.
title_fullStr Comparative Analysis of Deep Learning Approaches for Predicting EV Charging Station Loads: Spatial, Temporal, and Spatiotemporal Perspectives.
title_full_unstemmed Comparative Analysis of Deep Learning Approaches for Predicting EV Charging Station Loads: Spatial, Temporal, and Spatiotemporal Perspectives.
title_sort comparative analysis of deep learning approaches for predicting ev charging station loads: spatial, temporal, and spatiotemporal perspectives.
publishDate 2024
url http://utpedia.utp.edu.my/id/eprint/28676/
_version_ 1807051989030273024
score 13.214268

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