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Table of contents (8 chapters)
Keywords
About this book
The volume presents an introduction to neural nets that describes some of the basic concepts, as well as providing a more mathematical treatise for those wishing further details on neural net architecture. The bulk of the text, however, is devoted to descriptions of neural net applications in such broad-ranging fields as census analysis, predicting the spread of AIDS, describing synoptic controls on mountain snowfall, examining the relationships between atmospheric circulation and tropical rainfall, and the remote sensing of polar cloud and sea ice characteristics.
The text illustrates neural nets employed in modes analogous to multiple regression analysis, cluster analysis, and maximum likelihood classification. Not only are the neural nets shown to be equal or superior to these more conventional methods, particularly where the relationships have a strong nonlinear component, but they are also shown to contain significant explanatory power. Several chapters demonstrate that the nets themselves can be decomposed to illuminate causative linkages between different events in both the physical and human environments.
Editors and Affiliations
Bibliographic Information
Book Title: Neural Nets: Applications in Geography
Editors: Bruce C. Hewitson, Robert G. Crane
Series Title: GeoJournal Library
DOI: https://doi.org/10.1007/978-94-011-1122-5
Publisher: Springer Dordrecht
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media Dordrecht 1994
Hardcover ISBN: 978-0-7923-2746-2Published: 31 March 1994
Softcover ISBN: 978-94-010-4490-5Published: 23 October 2012
eBook ISBN: 978-94-011-1122-5Published: 06 December 2012
Series ISSN: 0924-5499
Series E-ISSN: 2215-0072
Edition Number: 1
Number of Pages: XI, 196
Topics: Geography, general, Complex Systems, Methodology of the Social Sciences, Statistical Physics and Dynamical Systems