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9780792327462: Neural Nets: Applications in Geography: v. 29 (Geojournal Library)
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ISBN 10: 0792327462 ISBN 13: 9780792327462
Editorial: Springer, 1994

Sinopsis

Preface. 1. Looks and Uses; B.C. Hewitson, R.G. Crane. 2. Neural Networks and Their Applications; E.E. Clothiaux, C.M. Bachmann. 3. Neuroclassification of Spatial Data; S. Openshaw. 4. Self Organizing Maps -- Application to Census Data; K. Winter, B.C. Hewitson. 5. Predicting Snowfall from Synoptic Circulation: a Comparison of Linear Regression and Neural Network Methodologies; D.L. McGinnis. 6. Neural Computing and the AIDS Pandemic: the Case of Ohio; P.G. Gould. 7. Precipitation Controls in Southern Mexico; B.C. Hewitson, R.G. Crane. 8. Classification of Arctic Cloud and Sea Ice Features in Multi-Spectral Satellite Data; J.R. Key. Appendix I: Neural Network Resources. Appendix II: Fortran 77 Listing for Kohonen Self Organizing Map.

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Reseña del editor

Neural nets offer a fascinating new strategy for spatial analysis, and their application holds enormous potential for the geographic sciences. However, the number of studies that have utilized these techniques is limited. This lack of interest can be attributed, in part, to lack of exposure, to the use of extensive and often confusing jargon, and to the misapprehension that, without an underlying statistical model, the explanatory power of the neural net is very low. Neural Nets: Applications for Geography attacks all three issues; the text demonstrates a wide variety of neural net applications in geography in a simple manner, with minimal jargon. 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.

Reseña del editor

Neural nets offer a new strategy for spatial analysis, and their application holds enormous potential for the geographic sciences. However, the number of studies that have utilized these techniques is limited. This lack of interest can be attributed, in part, to lack of exposure, to the use of extensive and often confusing jargon, and to the misapprehension that, without an underlying statistical model, the explanatory power of the neural net is very low. This text attacks all three issues, demonstrating a wide variety of neural net applications in geography in a simple manner, with minimal jargon. 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 wanting 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.

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Editorial
Springer
Año de publicación
1994
Idioma
Inglés
ISBN 10 
0792327462
ISBN 13 
9780792327462
Encuadernación
Tapa dura
Número de páginas
212
Editor
Hewitson B., Crane R.G.
Contacto del fabricante
Springer Nature Customer Service Center GmbH
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