Titlebook: Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling; Y. Z. Ma Book 2019 Springer Nature Switz

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Y. Z. Mahat is perhaps the best-known body of work on this topic: the preferential attachment model [9, 10], in which vertices are added to a network with edges that attach to pre-existing vertices with probabilities depending on those vertices’ degrees. When the attachment probability is precisely linear i

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Y. Z. Main particular a worm algorithm for O(N) relativistic models and methods for numerical analytic continuation of quantum Monte Carlo data. The predictions obtained are particularly relevant to recent experiments in cold atomic systems and disordered superconductors.978-3-319-37014-9978-3-319-19354-0Series ISSN 2190-5053 Series E-ISSN 2190-5061

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Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling

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Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling978-3-030-17860-4

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phasizes the integration of descriptive geology and quantitaEarth science is becoming increasingly quantitative in the digital age. Quantification of geoscience and engineering problems underpins many of the applications of big data and artificial intelligence. This book presents quantitative geosci