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The Application of Neural Networks in the Earth System Sciences

Neural Networks Emulations for Complex Multidimensional Mappings

  • The book provides a unifying systematic approach to these types of problems, considering them as nonlinear multidimensional mappings that can be emulated by NNs
  • The book introduces a basic mathematical concept of complex nonlinear mapping and offers a generic approach – NN emulation technique - for modeling such mappings
  • The book presents a detailed discussion of several types of practical, complex, real life applications developed by the author
  • The discussion helps the reader to understand general concepts and provides numerous technical details that are vitally important for practical implementation of presented methodology

Part of the book series: Atmospheric and Oceanographic Sciences Library (ATSL)

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Table of contents (6 chapters)

  1. Front Matter

    Pages i-xvii
  2. Introduction

    • Vladimir M. Krasnopolsky
    Pages 1-11
  3. Introduction to Mapping and Neural Networks

    • Vladimir M. Krasnopolsky
    Pages 13-46
  4. Atmospheric and Oceanic Remote Sensing Applications

    • Vladimir M. Krasnopolsky
    Pages 47-79
  5. NN Ensembles and Their Applications

    • Vladimir M. Krasnopolsky
    Pages 145-180
  6. Conclusions

    • Vladimir M. Krasnopolsky
    Pages 181-186
  7. Back Matter

    Pages 187-189

About this book

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 ofbest 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)




 

Reviews

 “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)

"The author’s unique perspective that a theoretical physicist and an environmental scientist makes this book a well-balanced combination of a NN theory and practical applications in two main areas, numerical climate/weather models andsatellite remote sensing areas, in which the author has made significant contributions. (...) Among many interesting and practical NN applications, several very important oceanic NN applications, in satellite remote sensing (forward and inverse problems), in ocean wind wave models, and in ocean data assimilation systems, are presented in the book.  These and other examples demonstrate the power and flexibility of the NN technique and show how to apply this technique to real life problems. (Prof. Isaac Ginis, University of Rhode Island, USA)

Authors and Affiliations

  • Prediction, NOAA Center for Weather and Climate, College Park, USA

    Vladimir M. Krasnopolsky

Bibliographic Information

Buy it now

Buying options

eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access