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Record Nr. |
UNINA9910426056103321 |
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Titolo |
Encyclopedia of Mathematical Geosciences [[electronic resource] /] / edited by B.S. Daya Sagar, Qiuming Cheng, Jennifer McKinley, Frits Agterberg |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
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ISBN |
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Collana |
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Encyclopedia of Earth Sciences Series, , 1388-4360 |
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Disciplina |
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Soggetti |
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Geology—Statistical methods |
Mathematical physics |
Remote sensing |
Statistics |
Quantitative Geology |
Mathematical Applications in the Physical Sciences |
Remote Sensing/Photogrammetry |
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences |
Statistics and Computing/Statistics Programs |
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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 contenuto |
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Artificial Intelligence -- Bigdata -- Chaos and Singularity Analysis in Geosciences -- Compositional Data Analysis -- Computational Geosciences -- Digital Image Processing and Analysis -- Fractals and Multifractals -- Fuzzy and Rough Set Theory in Geosciences -- Geographical Information Science -- Geomathematics -- Geostatistics -- Inversion Theory -- Kriging -- Machine Learning and Geosciences -- Mathematical Morphology -- Mathematical Petrology -- Morphometry and Hypsometry -- Multiple Point Statistics -- Neural Networks -- Signal Processing and Analysis -- Spatial Data Sciences -- Spatial Statistics -- Stochastic -- Wavelets in Geosciences. |
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Sommario/riassunto |
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The Encyclopedia of Mathematical Geosciences is a complete and authoritative reference work. It provides concise explanation on each |
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term that is related to Mathematical Geosciences. Over 300 international scientists, each expert in their specialties, have written over 300 separate articles on different topics of mathematical geosciences including contributions on Artificial Intelligence, Big Data, Compositional Data Analysis, Geomathematics, Geostatistics, Mathematical Morphology, Mathematical Petrology, Multifractals, Multiple Point Statistics and Stochastic Process Modeling. Each topic incorporates cross-referencing to related articles, and also has its own reference list to lead the reader to essential articles within the published literature. The entries are arranged alphabetically, for easy access, and the subject and author indices are comprehensive and extensive. |
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