irenekarijadi/RF-LSTM-CEEMDAN
Building energy consumption prediction using hybrid RF-LSTM based CEEMDAN method
This project helps building managers and facility operators accurately predict future energy consumption in various building types. By inputting historical energy usage data, it outputs highly precise energy consumption forecasts. This is designed for professionals focused on optimizing building energy management and operational efficiency.
No commits in the last 6 months.
Use this if you need to make highly accurate predictions of building energy usage to inform management decisions, especially for buildings with complex, non-linear energy consumption patterns.
Not ideal if you need a real-time energy monitoring system or a simple tool for basic energy budgeting without complex predictive analytics.
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36
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5
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Mar 18, 2022
Commits (30d)
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