{"id":28221124,"url":"https://github.com/visvav/time-series-forecasting","last_synced_at":"2026-03-04T14:02:17.997Z","repository":{"id":283157701,"uuid":"950875945","full_name":"VisvaV/Time-Series-Forecasting","owner":"VisvaV","description":"A web-based application for analyzing historical weather data and forecasting future trends using advanced statistical models. 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It utilizes various statistical models like ARIMA and SARIMA to predict temperature trends. The application includes a web interface to visualize and forecast temperature data.\n\n## Features\n\n- **Time Series Visualization**: Plots time series data for better understanding.\n- **Moving Averages**: Calculates Simple, Cumulative, and Exponential Moving Averages.\n- **ACF/PACF Plots**: Displays Autocorrelation and Partial Autocorrelation plots.\n- **ARIMA/SARIMA Forecasting**: Predicts future temperature values using ARIMA and SARIMA models.\n- **Stationarity Tests**: Performs Augmented Dickey-Fuller and KPSS tests for stationarity.\n- **Metrics Calculation**: Computes Mean Absolute Error, Root Mean Squared Error, and Mean Absolute Percentage Error.\n\n## Requirements\n\nSee [requirements.txt](requirements.txt) for dependencies.\n\n## Documentation\n\nFor detailed theory on time series forecasting, see [Documentation.md](Documentation.md).\n\n## Team Details\n\nSee [team_details.txt](team_details.txt) for team information.\n\n## Deployment\n\nThe application is deployed on Render and can be accessed at:\n[https://time-series-forecasting-3xih.onrender.com](https://time-series-forecasting-3xih.onrender.com)\n\n## Usage\n\n1. Clone the repository.\n2. Install dependencies using `pip install -r requirements.txt`.\n3. Run the application with `python app.py`.\n4. Open a web browser and navigate to `http://127.0.0.1:5000/`.\n\n## Contributing\n\nContributions are welcome. Please submit a pull request with your changes.\n\n## License\n\nThis project is licensed under the MIT License. See [LICENSE](LICENSE) for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvisvav%2Ftime-series-forecasting","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvisvav%2Ftime-series-forecasting","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvisvav%2Ftime-series-forecasting/lists"}