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Sunday, May 10, 2020 | History

1 edition of Neural Nets: Applications in Geography found in the catalog.

Neural Nets: Applications in Geography

by Bruce C. Hewitson

  • 351 Want to read
  • 9 Currently reading

Published by Springer Netherlands in Dordrecht .
Written in English

    Subjects:
  • Methodology,
  • Cartography,
  • Social sciences,
  • Geography

  • About the Edition

    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.

    Edition Notes

    Statementedited by Bruce C. Hewitson, Robert G. Crane
    SeriesThe GeoJournal Library -- 29, GeoJournal library -- 29.
    ContributionsCrane, Robert G.
    Classifications
    LC ClassificationsG1-922
    The Physical Object
    Format[electronic resource] /
    Pagination1 online resource (xi, 196 pages).
    Number of Pages196
    ID Numbers
    Open LibraryOL27076985M
    ISBN 109401044902, 9401111227
    ISBN 109789401044905, 9789401111225
    OCLC/WorldCa851393479

    The text provides an introduction to expert systems, neural nets, genetic algorithms, smart systems and artificial life and shows how they are likely to transform geographical enquiry. An integral disk provides examples and exercises for the readers to try themselves, which is a major methodological milestone in by: The main goal of this Special Issue is to collect papers regarding state-of-the-art and the latest studies on neural networks and learning systems. Moreover, it is an opportunity to provide a place where researchers will be able to share and exchange their views on this topic in the fields of theory, design, and applications.

    Modern neural nets provide an interesting example. For the ImageIdentify function of the Wolfram Language we’ve trained a neural net to identify thousands of kinds of things in the world. Thomas Esch received the Diploma in applied physical geography from the University of Trier, Trier, Germany, in , and the Ph.D. degree in physical geography and remote sensing from the University of Wuerzburg, Germany, in

    Neural Networks and Learning Machines, 3rd Edition. Real-life Data: Case studies include US Postal Service Data for semiunsupervised learning using the Laplacian RLS Algorithm, how PCA is applied to handwritten digital data, the analysis of natural images by using sparse-sensory coding and ICA, dynamic reconstruction applied to the Lorenz attractor by using a regularized Format: On-line Supplement. • Implement deep learning models and neural networks with Python Book Description The number of applications of deep learning and neural networks has multiplied in the last couple of years. Neural nets has enabled significant breakthroughs in everything from computer vision, voice generation, voice recognition and self-driving cars.


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Neural Nets: Applications in Geography by Bruce C. Hewitson Download PDF EPUB FB2

Neural Nets: Applications for Geography attacks all three issues; the text demonstrates a wide variety Neural Nets: Applications in Geography book 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. 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 Brand: Springer Netherlands. Demonstrating a variety of neural net applications in geography in a simple manner, this text presents an introduction to neural nets that describes some of the basic concepts, as well as providing a Read more.

Get this from a library. Neural Nets: Applications in Geography. [Bruce C Hewitson; Robert G Crane] -- 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. 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 Manufacturer: Springer.

The text provides an introduction to expert systems, neural nets, genetic algorithms, smart systems and artificial life and shows how they are likely to transform geographical enquiry. A major methodological milestone in geography; The first geographical book Price: $ 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 Brand: Springer Netherlands. Abstract. The current interest in artificial neural networks can be attributed, in part, to the development of the modern computer.

Since the advent of inexpensive, efficient, highstorage capacity computers, there has been an information explosion in many scientific disciplines as researchers are able to acquire larger and more comprehensive data by: 8. Scientific Applications of Neural Nets Proceedings of the th W.E.

Heraeus Seminar Held at Bad Honnef, Germany, 11–13 May Editors: Clark, John W., Lindenau, Thomas, Ristig, Manfred L. (Eds.). This unique work introduces the basic principles of artificialintelligence with applications in geographical teaching andresearch, GIS, and planning.

Written in an accessible,non-technical and witty style, this book marks the beginning of theAl revolution in geography with major implications for teaching andresearch.

The authors provide an easy to understand. This unique work introduces the basic principles of artificial intelligence with applications in geographical teaching and research, GIS, and planning.

Written in an accessible, non-technical and witty style, this book marks the beginning of the Al revolution in geography with major implications for teaching and research. The authors provide an easy to understand basic. The most common applications of neural networks in remote sensing are considered, particularly those concerned with the classification of land and clouds, and.

The text provides an introduction to expert systems, neural nets, genetic algorithms, smart systems and artificial life and shows how they are likely to transform geographical enquiry. An integral disk provides examples and exercises for the readers to try themselves, which is a major methodological milestone in geography.

Neural Network Applications in Control by G. Irwin,available at Book Depository with free delivery worldwide/5(3).

From the Publisher: The text provides an introduction to expert systems, neural nets, genetic algorithms, smart systems and artificial life and shows how they are likely to transform geographical enquiry.

An integral disk provides examples and exercises for the readers to try themselves, which is a major methodological milestone in geography. The authors provide an. State-of-the-art coverage of Kalman filter methods for the design of neural networksThis self-contained book consists of seven chapters by expert contributors that discuss Kalman filtering as applied to the training and use of neural networks.

Although the traditional approach to the subject is almost always linear, this book recognizes and. The text provides an introduction to expert systems, neural nets, genetic algorithms, smart systems and artificial life and shows how they are likely to transform geographical enquiry.

A major methodological milestone in geography; The first geographical book Author: Openshaw. A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text.

UGC NET Paper-2 Syllabus Continues The following part of the UGC NET syllabus were previously under UGC NET Paper-3, Part-B, however, as UGC has now only two papers i.e. UGC NET Paper-1 which is general and compulsory for all subjects and UGC NET Paper-2 on the specif i c subject (including all electives, without options) instead of previous three papers i.e.

I am not a cognitive scientist, and this book is a bit technical, but it is still within reach of the motivated lay person. Gardenfors puts forward a a model to explain cognition that he calls "conceptual spaces." These conceptual spaces are at a level of abstraction in between the symbolic (used by AI types) and connectionist (Neural Nets).Cited by:.

NEURAL NETS: Applications in Geography. Edited by BRUCE C. HEWITSON and ROBERT G. CRANE. xii and pp.; maps, diagrs., refs. Boston: Kluwer Academic Publishers, $ (cloth), ISBN Neural Nets exposes a geographical readership to a broad, relatively new field and achieves this goal with outstanding success.springer, This volume collects a selection of contributions which has been presented at the 22nd Italian Workshop on Neural Networks, the yearly meeting of the Italian Society for Neural Networks (SIREN).

The conference was held in Italy, Vietri sul Mare (Salerno), during MayThe annual meeting of SIREN is sponsored by International Neural Network Society .This book provides comprehensive coverage of neural networks, their evolution, their structure, the problems they can solve, and their applications.

The first half of the book looks at theoretical investigations on artificial neural networks and addresses the key architectures that are capable of implementation in various application scenarios.