书目名称 | The Application of Neural Networks in the Earth System Sciences | 副标题 | Neural Networks Emul | 编辑 | Vladimir M. Krasnopolsky | 视频video | | 概述 | 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 mathematica | 丛书名称 | Atmospheric and Oceanographic Sciences Library | 图书封面 |  | 描述 | .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 net | 出版日期 | Book 2013 | 关键词 | Atmospheric and Oceanic Numerical Modeling; Computation/Artificial Intelligence in Earth Sciences; Neu | 版次 | 1 | doi | https://doi.org/10.1007/978-94-007-6073-8 | isbn_softcover | 978-94-017-8465-8 | isbn_ebook | 978-94-007-6073-8Series ISSN 1383-8601 Series E-ISSN 2215-162X | issn_series | 1383-8601 | copyright | Springer Science+Business Media Dordrecht(outside the USA) 2013 2013 |
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