Energy Consumption Forecasting

Overview

Built a time series forecasting model using SARIMAX to predict energy consumption patterns. Implemented data preprocessing, model training, and evaluation with confidence intervals for predictions.

A sophisticated time series forecasting project that uses SARIMAX (Seasonal AutoRegressive Integrated Moving Average with eXogenous regressors) to predict energy consumption patterns. The model includes comprehensive data preprocessing, feature engineering, and provides confidence intervals for predictions. The project demonstrates advanced statistical modeling techniques and time series analysis.

Key Features

• SARIMAX model implementation
• Time series data preprocessing
• Seasonal pattern detection
• Confidence interval predictions
• Model evaluation metrics
• Data visualization and analysis

Technologies Used