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This book establishes brand-new frame theory and technical implementation in data science, with a special focus on spatial-scale feature extraction, network dynamics, object-oriented analysis, data-driven environmental prediction, and climate diagnosis. Given that data science is unanimously recognized as a core driver for achieving Sustainable Development Goals of the United Nations, these frame techniques bring fundamental changes to multi-channel data mining systems and support the development of digital Earth platforms. This book integrates the authors' frame research in the past twenty years and provides cutting-edge techniques and depth for scientists, professionals, and graduate students in data science, applied mathematics, environmental science, and geoscience.
| Autorius: | Palle E. T. Jorgensen, Zhihua Zhang, |
| Leidėjas: | Springer Nature Switzerland |
| Išleidimo metai: | 2024 |
| Knygos puslapių skaičius: | 264 |
| ISBN-10: | 3031494822 |
| ISBN-13: | 9783031494826 |
| Formatas: | 285 x 215 x 20 mm. Knyga kietu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Frame Theory in Data Science“
