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Record Nr. |
UNINA9910830444603321 |
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Titolo |
Advanced mapping of environmental data [[electronic resource] ] : geostatistics, machine learning, and Bayesian maximum entropy / / edited by Mikhail Kanevski |
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Pubbl/distr/stampa |
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London, : ISTE |
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Hoboken, N.J., : Wiley, 2008 |
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ISBN |
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9780470611463 (e-book) |
9781848210608 (hbk.) |
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Descrizione fisica |
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1 online resource (xiii, 313 p.) : ill |
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Collana |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Geology - Statistical methods |
Machine learning |
Bayesian statistical decision theory |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Chapter 1. Advanced Mapping of Environmental Data: Introduction -- Chapter 2. Environmental Monitoring Network Characterization and Clustering -- Chapter 3. Geostatistics: Spatial Predictions and Simulations -- Chapter 4. Spatial Data Analysis and Mapping Using Machine Learning Algorithms -- Chapter 5. Advanced Mapping of Environmental Spatial Data: Case Studies -- Chapter 6. Bayesian Maximum Entropy – BME -- Index. |
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Sommario/riassunto |
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This book combines geostatistics and global mapping systems to present an up-to-the-minute study of environmental data. Featuring numerous case studies, the reference covers model dependent (geostatistics) and data driven (machine learning algorithms) analysis techniques such as risk mapping, conditional stochastic simulations, descriptions of spatial uncertainty and variability, artificial neural networks (ANN) for spatial data, Bayesian maximum entropy (BME), and more. |
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