Computational Methods for Time-Series Analyses in Earth Sciences
Language: English
Published by Elsevier Inc Jul 2025, 2025
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 244.02
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Add to basketItem description from seller
Neuware - Computational Methods for Time-Series Analyses in Earth Sciences bridges the gap between theoretical knowledge and practical application, offering a deep dive into the utilization of R programming for managing, analyzing, and forecasting time-series data within the realm of Earth sciences. It systematically unfolds the layers of data manipulation, graphical representation, and sampling to prepare the reader for complex analyses and predictive modeling from the basics of signal processing to the nuances of machine learning. It presents cutting-edge techniques, such as neural networks, kernel-based methods, and evolutionary algorithms, specifically tailored to tackle challenges, and provides practical case studies to aid readers with utilizing the techniques covered.Computational Methods for Time-Series Analyses in Earth Sciences is a valuable resource for scientists, researchers, and students delving into the intricacies of Earth's environmental patterns and cycles through the lens of computational analysis and guides readers through various computational approaches to deciphering spatial and temporal data.…
Seller Inventory # 9780443336317
- Title
- Computational Methods for Time-Series Analyses in Earth Sciences
- Author
- Silvio Jos Gumiere
- Publisher
- Elsevier Inc Jul 2025
- Publication year
- 2025
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 0443336318
- ISBN 13
- 9780443336317
- Item weight
- 963 grams
- Dimensions
- 229x152x37 mm
Computational Methods for Time-Series Analyses in Earth Sciences is a valuable resource for scientists, researchers, and students delving into the intricacies of Earth's environmental patterns and cycles through the lens of computational analysis and guides readers through various computational approaches to deciphering spatial and temporal data.
- Focuses on the use of R for time-series analysis and the application of these methods directly to Earth and environmental datasets
- Integrates Machine Learning techniques, enabling readers to explore advanced computational methods for forecasting and modeling
- Includes case studies with real-world applications, providing readers with examples on how to translate computational skills into tangible outcomes
"Synopsis" may belong to another edition of this title.
About the Author
Dr. Hossein Bonakdari is a distinguished professor in the Department of Civil Engineering at the University of Ottawa, specializing in mathematical modeling and artificial intelligence (AI). A leading expert in AI-driven data analysis, he has pioneered advanced algorithms for real-time forecasting and big data interpretation, significantly improving the understanding and management of environmental systems.
Dr. Bonakdari has authored four books, published over 320 peer-reviewed journal articles, contributed to more than 20 book chapters, and delivered over 100 presentations at national and international conferences. As a respected editorial board member of several leading journals, he continues to shape research in his field. His groundbreaking contributions have earned him global recognition, ranking him among the top 2% of the world's scientists from 2019 to 2024.
"About the title" may belong to another edition of this title.
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