Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/157989
Title: Deep learning-based forecasting of electric vehicle (EV) charging station availability
Authors: Lim, Lee Son
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Lim, L. S. (2022). Deep learning-based forecasting of electric vehicle (EV) charging station availability. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157989
Abstract: In the modern urban intelligent transportation system, high accuracy prediction of the public transportation facilities usage condition can help drivers to arrange daily commute wisely. This project focuses on applying the advanced deep learning algorithm to forecast the EV charging station availability in one real world case. Related baseline methods will be also executed to compare the prediction performance across different horizons. By the end of this project, it is expected to develop the AI system to grasp the periodic behavior of charging and predict the long-term EV charging station availability with high accuracy. Spatial-Temporal Network based algorithm and Attention Mechanism based algorithm are good options.
URI: https://hdl.handle.net/10356/157989
Schools: School of Electrical and Electronic Engineering 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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