Advanced hydroinformatics : machine learning and optimization for water resources /

"During the last few decades, many environmental and hydrological problems have been represented and studied through data analysis and machine learning models. Machine learning evolves rapidly with new algorithms and new tools. Nowadays, complex problems are analyzed by identifying and explaini...

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Bibliographic Details
Other Authors: Corzo Perez, Gerald Augusto (Editor), Solomatine, Dimitri P. (Editor)
Format: eBook
Language:English
Published: [Washington, DC] : Hoboken, NJ : American Geophysical Union ; John Wiley & Sons, Inc., 2024.
Series:Special publications ; 78
Subjects:
Online Access:Connect to the full text of this electronic book
Description
Summary:"During the last few decades, many environmental and hydrological problems have been represented and studied through data analysis and machine learning models. Machine learning evolves rapidly with new algorithms and new tools. Nowadays, complex problems are analyzed by identifying and explaining patterns and anomalies of measured or simulated data. Understanding hydrological characteristics and subsequently predicting spatiotemporal hydrological events has developed largely. Temporal information is sometimes limited; spatial information, on the other hand, has increased in recent years due to technological advances including the availability of remote sensing data. These developments have motivated new research efforts to include data in model representation and analysis. Also, current trends and variability of hydrological extremes call for novel approaches of spatio-temporal and machine learning analysis to assess, predict, and manage water-related and/or interlinked hazards including the assessment of uncertainties"--
Physical Description:1 online resource (xiii, 461 pages) : illustrations (chiefly color), Maps (chiefly color).
Bibliography:Includes bibliographical references and index.
ISBN:9781119639329
1119639328
9781119639268
1119639263
9781119639343
1119639344