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Applied Intelligent Systems

New Directions

  • Book
  • © 2004

Overview

Editors:
  1. John Fulcher

    1. School of Information, Technology & Computer Science, University of Wollongong, Wollongong, Australia

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    You can also search for this editor in PubMed   Google Scholar

  2. Lakhmi C. Jain

    1. Knowledge-Based Intelligent, Engineering Systems Centre, University of South Australia, Adelaide, Australia

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • Provides practical examples of successful applications of Intelligent Systems to real world problems
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 153)

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Table of contents (10 chapters)

  1. Front Matter

    Pages I-XVII
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  2. Adaptive Technical Analysis in the Financial Markets Using Machine Learning: a Statistical View

    • David Edelman, Pam Davy
    Pages 1-16

  3. Higher Order Neural Networks for Satellite Weather Prediction

    • Ming Zhang, John Fulcher
    Pages 17-57

  4. Independent Component Analysis

    • Andrew D. Back
    Pages 59-95

  5. Regulatory Applications of Artificial Intelligence

    • Howard Copland
    Pages 97-132

  6. An Introduction to Collective Intelligence

    • Tim Hendtlass
    Pages 133-178

  7. Where are all the mobile robots?

    • Phillip J. McKerrow
    Pages 179-200

  8. Building Intelligent Legal Decision Support Systems: Past Practice and Future Challenges

    • John Zeleznikow
    Pages 201-254

  9. Teaming Humans and Intelligent Agents

    • Christos Sioutis, Pierre Urlings, Jeffrey Tweedale, Nikhil Ichalkaranje
    Pages 255-279

  10. Fuzzy Multivariate Auto-Regression Method and its Application

    • N. Arzu Sisman-Yilmaz, Ferda N. Alpaslan, Lakhmi C. Jain
    Pages 281-300

  11. Selective Attention Adaptive Resonance Theory and Object Recognition

    • Peter Lozo, Jason Westmacott, Quoc V. Do, Lakhmi C. Jain, Lai Wu
    Pages 301-320

  12. Back Matter

    Pages 321-325
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Keywords

About this book

Humans have always been hopeless at predicting the future…most people now generally agree that the margin of viability in prophecy appears to be 1 ten years. Even sophisticated research endeavours in this arena tend to go 2 off the rails after a decade or so. The computer industry has been particularly prone to bold (and often way off the mark) predictions, for example: ‘I think there is a world market for maybe five computers’ Thomas J. Watson, IBM Chairman (1943), ‘I have traveled the length and breadth of this country and talked with the best people, and I can assure you that data processing is a fad that won’t last out the year’ Prentice Hall Editor (1957), ‘There is no reason why anyone would want a computer in their home’ Ken Olsen, founder of DEC (1977) and ‘640K ought to be enough for anybody’ Bill Gates, CEO Microsoft (1981). 3 The field of Artificial Intelligence – right from its inception – has been particularly plagued by ‘bold prediction syndrome’, and often by leading practitioners who should know better. AI has received a lot of bad press 4 over the decades, and a lot of it deservedly so. How often have we groaned in despair at the latest ‘by the year-20xx, we will all have…(insert your own particular ‘hobby horse’ here – e. g.

Editors and Affiliations

  • School of Information, Technology & Computer Science, University of Wollongong, Wollongong, Australia

    John Fulcher

  • Knowledge-Based Intelligent, Engineering Systems Centre, University of South Australia, Adelaide, Australia

    Lakhmi C. Jain

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