Wavelet-Neural-Network

WNN implementation for forecasting electricity consumption This project proposes a method for forecasting the monthly electrical consumption is an attempt to optimize energy production by predicting the electricity consumption based on the past data by implementing the stochastic recurrent network. It implements DWT which is used to extract information from the signal in combination with Stochastic Recurrent Wavelet Neural Network (SRWNN) where the information is fed to predict the consumptions based on the past data signal.

Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
Approx.csv		Approx.csv
Approx_data.csv		Approx_data.csv
Data_preprocess.ipynb		Data_preprocess.ipynb
Decomp.csv		Decomp.csv
Decomp_data.csv		Decomp_data.csv
Predictions.csv		Predictions.csv
README.md		README.md
Untitled.ipynb		Untitled.ipynb
crude.csv		crude.csv
crude_data.ipynb		crude_data.ipynb
crude_pred.ipynb		crude_pred.ipynb
data.csv		data.csv
data_prep.py		data_prep.py
fig.png		fig.png
paper_data.ipynb		paper_data.ipynb
train.csv		train.csv
training.py		training.py

akshat654/Wavelet-Neural-Network

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Wavelet-Neural-Network

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