Sustainability-driven hourly energy demand forecasting in Bangladesh using Bi-LSTMs

Sustainability-driven hourly energy demand forecasting in Bangladesh using Bi-LSTMs

This research presents a comprehensive study on developing and evaluating a deep learning-based forecasting model for hourly energy demand prediction in Bangladesh. Leveraging a novel dataset obtained from the Power Grid Company of Bangladesh (PGCB), the proposed model utilizes bi-directional long s...

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Bibliographic Details
Main Authors: Ullah Miah, Md Saef, Islam, Md Imamul, Islam, Saiful, Ahmed, Ahanaf, Rahman, Mushfiqur Mahabubur, Mahmud, Mufti R.
Format: Conference or Workshop Item
Language:English
Published: Elsevier B.V. 2024
Subjects:
T Technology (General)
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/41731/
http://umpir.ump.edu.my/id/eprint/41731/1/Sustainability-driven%20hourly%20energy%20demand%20forecasting%20in%20Bangladesh%20using%20Bi-LSTMs.pdf

Internet

http://umpir.ump.edu.my/id/eprint/41731/
http://umpir.ump.edu.my/id/eprint/41731/1/Sustainability-driven%20hourly%20energy%20demand%20forecasting%20in%20Bangladesh%20using%20Bi-LSTMs.pdf

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