The deadline to submit a session, town hall, or pre-conference workshop proposal for AGU25 has passed. Please search for and review proposed sessions below. Please note this site is frozen as of 4/29/25 and will not reflect any changes to proposals made after this date.


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Abstract: Forecasting Hourly Electrical Load Demand: A Comparative Study of XGBoost and Bi-LSTM Models (AGU25)

Forecasting Hourly Electrical Load Demand: A Comparative Study of XGBoost and Bi-LSTM Models

Saptaporna Dey1, Atika Alam1 and Sujoy Dey2, (1)Bangladesh University of Engineering and Technology, Department of Industrial and Production Engineering, Dhaka, Bangladesh, (2)Bangladesh University of Engineering and Technology, Department of Water Resources Engineering, Dhaka, Bangladesh
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