Mathematical Geosciences publishes original, high-quality, interdisciplinary papers in geomathematics and related data science, including: Mathematical models, algorithms and computational frameworks, their implementation aspects, and real-life applications. The journal encourages publications emphasizing new developments, concepts and tools in big data and their analytics, processing, integration and assimilation, computational intelligence, machine learning and data-driven modelling, for studies of the Earth, its natural resources and the environment. Publication of method’s code and datasets demonstrating their application are welcome and available as online supplementary material. Publication of method code and datasets demonstrating application are welcome and are provided as online supplementary material.
This international publication is the official journal of the IAMG. Mathematical Geosciences is an essential reference for researchers and practitioners of geomathematics, related models, algorithms and computing, who develop and apply data science methods and quantitative models to earth science and geo-engineering problems.
Sampling Strategies for Uncertainty Reduction in Categorical Random Fields: Formulation, Mathematical Analysis and Application to Multiple-Point Simulations
Julián M. Ortiz (January 2019)
- Journal Title
- Mathematical Geosciences
- Volume 1 / 1969 - Volume 51 / 2019
- Print ISSN
- Online ISSN
- Springer Berlin Heidelberg
- Additional Links
- Industry Sectors
|Previous Title||Print ISSN||Online ISSN|
|Journal of the International Association for Mathematical Geology||0020-5958||1573-8868|
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