Beschreibung
Produktdetails
Einband
Taschenbuch
Erscheinungsdatum
01.10.2026
Verlag
ElsevierSeitenzahl
825
Maße (L/B)
23,5/19,1 cm
Gewicht
450 g
Sprache
Englisch
ISBN
978-0-443-51004-5
Big Data Mining and Machine Learning in Geoscience offers a comprehensive overview of the latest techniques and applications of data science in the geosciences, addressing the challenges of managing and interpreting vast and complex datasets. The book begins with foundational concepts in data cleaning and preprocessing, essential for ensuring the quality and reliability of geoscientific data. It then explores dimensionality reduction methods designed to simplify high-dimensional data without losing critical information, facilitating more efficient analysis. The text covers classification and prediction techniques that enable the identification of patterns and forecasting of geological phenomena. Graphical data processing and handling of infinite stream data and time series are discussed, highlighting their importance in real-time monitoring and dynamic systems analysis. The book explores advanced machine learning and deep learning methods, showcasing their transformative impact on geoscientific research. It also introduces knowledge graphs and large language models as emerging tools that enhance data integration, interpretation, and discovery. AI-driven geology is presented as a forward-looking approach that leverages artificial intelligence to revolutionize traditional geological practices, offering improved accuracy and insight. Throughout, practical examples and case studies illustrate how these technologies can be applied to solve complex problems in geoscience. This book equips researchers, practitioners, and students with cutting-edge knowledge and tools to harness big data and machine learning, driving innovation and deeper understanding in geoscience disciplines.
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