Tetuan City Electricity Consumption High-Frequency Time-Series Forecasting Using Arima, UCM, Machine Learning (Random Forest and k-NN), and Deep Learning (GRU Recurrent Neural Network) Models.
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Updated
Nov 7, 2023
Tetuan City Electricity Consumption High-Frequency Time-Series Forecasting Using Arima, UCM, Machine Learning (Random Forest and k-NN), and Deep Learning (GRU Recurrent Neural Network) Models.
I have performed a time series analysis of the stock prices of Tata Consultancy Services from 2002 to 2021. I have started by visualising the data. And then I fitted models like an autoregressive integrated moving average (ARIMA) model, Vector autoregression (VAR), SARIMA (seasonal ARIMA) model, UCM, and Dynamic Factor models.
Time Series Analysis and Forecasting (using ARIMA, UCM and Random Forest models) of a restaurant's revenue during the first lockdown of the COVID-19 pandemic in Italy, to estimate the loss incurred.
High-frequency time series forecast of electricity consumptions using ARIMA, UCM and ML techniques
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