Advanced Hydroinformatics
Machine Learning and Optimization for Water Resources
Gerald Augusto Corzo Corzo Perez – Editor (IHE Delft Institute for Water Education)
Dmitri Solomatine – Editor (IHE Delft Institute for Water Education, Water Problems Institute of Russian Academy of Sciences, TU Delft - Water Resources)
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Abstract
The rapid development of machine learning brings new possibilities for hydroinformatics research and practice with its ability to handle big data sets, identify patterns and anomalies in data, and provide more accurate forecasts.
Advanced Hydroinformatics: Machine Learning and Optimization for Water Resources presents both original research and practical examples that demonstrate how machine learning can advance data analytics, accuracy of modeling and forecasting, and knowledge discovery for better water management.
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