The Application of Neural Networks in the Earth System Sciences

The Application of Neural Networks in the Earth System Sciences

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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 a€“ 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. a€œThis 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.a€ (Prof. William W. Hsieh, University of British Columbia, Vancouver, Canada) a€œVladimir Krasnopolsky has been the a€œfounding fathera€ 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.a€ (Dr. Sue Ellen Haupt, National Center for Atmospheric Research, Boulder, USA) a€œVladimir 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.q a€ (Prof. Eugenia Kalnay, University of Maryland, USA)... universal approximators, i.e., they can approximate any continuous function to any predetermined accuracy (DeVore ... (weights) requires the solution of a large, nonlinear optimization problem, which can deliver suboptimal solutions. ... In our use of NN emulations, we also notice that NNs can sometimes exhibit relatively large errors (however, with small probability) ... 6.2 Comments About Other Statistical Learning Techniques The major SLTs 6.1 Comments About NN Technique 183.

Title:The Application of Neural Networks in the Earth System Sciences
Author: Vladimir M. Krasnopolsky
Publisher:Springer Science & Business Media - 2013-06-14

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