Implements weather station class in Python that calculates ETo (reference crop's evapotranspiration) based on UN-FAO Irrigation and Drainage Paper 56
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Updated
Jan 10, 2024 - Python
Implements weather station class in Python that calculates ETo (reference crop's evapotranspiration) based on UN-FAO Irrigation and Drainage Paper 56
Water-Futures Team implementation of the Battle of the Water Demand Forecasting
Evapotranspiration for the reference crop in Uzbekistan. Based on UN-FAO's Irrigation and Drainage Paper 56 and Penman-Monteith Equation.
Implements weather station class in C++ that calculates ETo based on Penman-Monteith equation
Evapotranspiration forecasting using FBProphet and NeuralProphet.
This project is for forecasting water demand using LSTM, deep learning algorithm. A dashboard is created using the predictions for decision making using Streamlit
Python analysis of NYCHA water billing data (2013–2025): cleaning, daily-use metric, borough trends, and visualizations.
💧 | A real-world application of the Edmonds-Karp algorithm for optimizing a water management system
Annual water demand and cost forecast for the Northern Virginia data-center corridor (Loudoun and Prince William counties), 2000–2030.
AI-powered water demand forecasting dashboard using Machine Learning and Streamlit.
Water demand forecasting system using an LSTM neural network and Streamlit dashboard for country-level water consumption analysis, trend visualization, cross-country comparison, and short-term demand prediction.
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