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The Application of Neural Networks in the Earth System Sciences - Neural Networks Emulations for Complex Multidimensional Mappings (Paperback, Softcover reprint of the original 1st ed. 2013) Loot Price: R3,518
Discovery Miles 35 180
The Application of Neural Networks in the Earth System Sciences - Neural Networks Emulations for Complex Multidimensional...

The Application of Neural Networks in the Earth System Sciences - Neural Networks Emulations for Complex Multidimensional Mappings (Paperback, Softcover reprint of the original 1st ed. 2013)

Vladimir M Krasnopolsky

Series: Atmospheric and Oceanographic Sciences Library, 46

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Loot Price R3,518 Discovery Miles 35 180 | Repayment Terms: R330 pm x 12*

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This book brings together a representative set of Earth System Science (ESS) applications of the neural network (NN) technique. It examines a progression of atmospheric and oceanic problems, which, from the mathematical point of view, can be formulated as complex, multidimensional, and nonlinear mappings. It is shown that these problems can be solved utilizing a particular type of NN - the multilayer perceptron (MLP). This type of NN applications covers the majority of NN applications developed in ESSs such as meteorology, oceanography, atmospheric and oceanic satellite remote sensing, numerical weather prediction, and climate studies. The major properties of the mappings and MLP NNs are formulated and discussed. Also, the book presents basic background for each introduced application and provides an extensive set of references. "This is an excellent book to learn how to apply artificial neural network methods to earth system sciences. The author, Dr. Vladimir Krasnopolsky, is a universally recognized master in this field. With his vast knowledge and experience, he carefully guides the reader through a broad variety of problems found in the earth system sciences where neural network methods can be applied fruitfully. (...) The broad range of topics covered in this book ensures that researchers/graduate students from many fields (...) will find it an invaluable guide to neural network methods." (Prof. William W. Hsieh, University of British Columbia, Vancouver, Canada) "Vladimir Krasnopolsky has been the "founding father" of applying computation intelligence methods to environmental science; (...) Dr. Krasnopolsky has created a masterful exposition of a young, yet maturing field that promises to advance a deeper understanding of best modeling practices in environmental science." (Dr. Sue Ellen Haupt, National Center for Atmospheric Research, Boulder, USA) "Vladimir Krasnopolsky has written an important and wonderful book on applications of neural networks to replace complex and expensive computational algorithms within Earth System Science models. He is uniquely qualified to write this book, since he has been a true pioneer with regard to many of these applications. (...) Many other examples of creative emulations will inspire not just readers interested in the Earth Sciences, but any other modeling practitioner (...) to address both theoretical and practical complex problems that may (or will!) arise in a complex system." " (Prof. Eugenia Kalnay, University of Maryland, USA)

General

Imprint: Springer
Country of origin: Netherlands
Series: Atmospheric and Oceanographic Sciences Library, 46
Release date: July 2015
Authors: Vladimir M Krasnopolsky
Dimensions: 235 x 155 x 11mm (L x W x T)
Format: Paperback
Pages: 189
Edition: Softcover reprint of the original 1st ed. 2013
ISBN-13: 978-9401784658
Categories: Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematical modelling
Books > Earth & environment > Earth sciences > The hydrosphere > Oceanography (seas)
Books > Earth & environment > Geography > Cartography, geodesy & geographic information systems (GIS) > Geographical information systems (GIS)
Books > Earth & environment > Geography > Cartography, geodesy & geographic information systems (GIS) > Remote sensing
Books > Computing & IT > Applications of computing > Artificial intelligence > General
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LSN: 9401784655
Barcode: 9789401784658

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