The Application of Neural Networks in the Earth System Sciences
Springer (Verlag)
978-94-017-8465-8 (ISBN)
“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)
Introduction.- Introduction to Mapping and Neural Networks.- Mapping Examples.- Some Generic Properties of Mappings.- MLP NN – A Generic Tool for Modeling Nonlinear Mappings.- Advantages and Limitations of the NN TechniqueNN Emulations.- Final remarks.- Atmospheric and Oceanic Remote Sensing Applications.- Deriving Geophysical Parameters from Satellite Measurements: Conventional Retrievals and Variational Retrievals.- NNs for Emulating Forward Models.- NNs for Solving Inverse Problems: NNs Emulating Retrieval Algorithms.-Controlling the NN Generalization and Quality Control of Retrievals.- Neural Network Emulations for SSM/I Data.- Using NNs to Go Beyond the Standard Retrieval Paradigm.- Discussion.-Applications of NNs to Developing Hybrid Earth System Numerical Models for Climate and Weather.- Numerical Modeling Background.- Hybrid Model Component and a Hybrid Model.- Atmospheric NN Applications.- An Ocean Application of the Hybrid Model Approach: Neural Network Emulation of Nonlinear Interactions in Wind Wave Models.- Discussion.- NN Ensembles and their applications.- Using NN Emulations of Dependencies between Model Variables in DAS.- NN nonlinear multi-model ensembles.- Perturbed physics and ensembles with perturbed physics.- Conclusions.- Comments about NN Technique.- Comments about other Statistical Learning Techniques.
“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)
| Erscheint lt. Verlag | 15.7.2015 |
|---|---|
| Reihe/Serie | Atmospheric and Oceanographic Sciences Library ; 46 |
| Zusatzinfo | XVII, 189 p. |
| Verlagsort | Dordrecht |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
| Naturwissenschaften ► Geowissenschaften ► Geografie / Kartografie | |
| Naturwissenschaften ► Geowissenschaften ► Geologie | |
| Naturwissenschaften ► Geowissenschaften ► Hydrologie / Ozeanografie | |
| Naturwissenschaften ► Geowissenschaften ► Meteorologie / Klimatologie | |
| Schlagworte | Atmospheric and Oceanic Numerical Modeling • Computation/Artificial Intelligence in Earth Sciences • Neural networks • Satellite Remote Sensing • Statistical Ensembles |
| ISBN-10 | 94-017-8465-5 / 9401784655 |
| ISBN-13 | 978-94-017-8465-8 / 9789401784658 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
aus dem Bereich
