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Encyclopedia of Mathematical Geosciences - B. S. Daya Sagar - Bog

Bag om Encyclopedia of Mathematical Geosciences

The Encyclopedia of Mathematical Geosciences is a complete and authoritative reference work. It provides concise explanation on each term that is related to Mathematical Geosciences. Over 300 international scientists, each expert in their specialties, have written around 350 separate articles on different topics of mathematical geosciences including contributions on Artificial Intelligence, Big Data, Compositional Data Analysis, Geomathematics, Geostatistics, Geographical Information Science, Mathematical Morphology, Mathematical Petrology, Multifractals, Multiple Point Statistics, Spatial Data Science, Spatial 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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  • Sprog:
  • Engelsk
  • ISBN:
  • 9783030850395
  • Indbinding:
  • Hardback
  • Sideantal:
  • 1812
  • Udgivet:
  • 21. juni 2023
  • Udgave:
  • 23001
  • Størrelse:
  • 215x101x285 mm.
  • Vægt:
  • 5360 g.
  • Ukendt - mangler pt..

Normalpris

  • BLACK WEEK

Medlemspris

Prøv i 30 dage for 45 kr.
Herefter fra 79 kr./md. Ingen binding.

Beskrivelse af Encyclopedia of Mathematical Geosciences

The Encyclopedia of Mathematical Geosciences is a complete and authoritative reference work. It provides concise explanation on each term that is related to Mathematical Geosciences. Over 300 international scientists, each expert in their specialties, have written around 350 separate articles on different topics of mathematical geosciences including contributions on Artificial Intelligence, Big Data, Compositional Data Analysis, Geomathematics, Geostatistics, Geographical Information Science, Mathematical Morphology, Mathematical Petrology, Multifractals, Multiple Point Statistics, Spatial Data Science, Spatial 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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