Applying machine learning and optimization technologies to water management problems
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.
Volume Highlights Include:
* Overview of the application of artificial intelligence and machine learning techniques in hydroinformatics
* Advances in modeling hydrological systems
* Different data analysis methods and models for forecasting water resources
* New areas of knowledge discovery and optimization based on using machine learning techniques
* Case studies from North America, South America, the Caribbean, Europe, and Asia
The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.
Autorentext
Gerald A. Corzo Perez, IHE Delft Institute for Water Education, The Netherlands
Dimitri P. Solomatine, IHE Delft Institute for Water Education, and Delft University of Technology, The Netherlands, and Water Problems Institute of the Russian Academy of Sciences, Moscow, Russia