ritikdhame / Electricity_Demand_and_Price_forecasting

Building Time series forecasting models, including the XGboost Regressor, GRU (Gated Recurrent Unit), LSTM (Long Short-Term Memory), CNN (Convolutional Neural Network), CNN-LSTM, and LSTM-Attention. Additionally, hybrid models like GRU-XGBoost and LSTM-Attention-XGBoost for Electricity Demand and price prediction

Date Created 2023-07-18 (about a year ago)

Commits 2 (last one about a year ago)

Stargazers 40 (0 this week)

Watchers 2 (0 this week)

Forks 6

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RepositoryStats indexes 579,555 repositories, of these ritikdhame/Electricity_Demand_and_Price_forecasting is ranked #509,093 (12th percentile) for total stargazers, and #476,089 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #13,910/16,901.

ritikdhame/Electricity_Demand_and_Price_forecasting is also tagged with popular topics, for these it's ranked: cnn (#488/540)

All Topics

cnn gru lstm cnn-lstm lstm-attention xgboost-regression

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2 commits on the default branch (main) since jan '22

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updated: 2024-10-24 @ 03:41pm, id: 667971594 / R_kgDOJ9BwCg