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 61 (0 this week)

Watchers 1 (0 this week)

Forks 9

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RepositoryStats indexes 628,089 repositories, of these ritikdhame/Electricity_Demand_and_Price_forecasting is ranked #427,517 (32nd percentile) for total stargazers, and #554,057 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #11,150/18,867.

ritikdhame/Electricity_Demand_and_Price_forecasting is also tagged with popular topics, for these it's ranked: cnn (#409/571)

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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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The only known language in this repository is Jupyter Notebook

updated: 2025-03-13 @ 04:25pm, id: 667971594 / R_kgDOJ9BwCg