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Knowledge-Based Systems in Astronomy [electronic resource] / edited by A. Heck, F. Murtagh.

Contributor(s): Material type: TextTextSeries: Lecture Notes in Physics ; 329Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 1989Description: IV, 284 p. 38 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540461395
Other title:
  • With contributions by numerous experts
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 520 23
LOC classification:
  • QB4
Online resources:
Contents:
Artificial intelligence applications for Hubble Space Telescope operations -- Knowledge based telescope scheduling -- Survey work with automated data analysis -- Distributed point-pattern matching -- Decision problems in the search for periodicities in gamma-ray astronomy. How can A.I. help? -- Classification and knowledge -- WOLF — A computer expert system for sunspot classification and solar flare prediction -- Knowledge based classification of galaxies -- Classification of IUE spectra: A rule based approach -- Representation of knowledge using Fuzzy set theory -- An approach to heuristic exploitation of astronomers' knowledge in automatic interpretation of optical pictures -- Connectionism and neural networks -- Applications of AI in astronomy: A view towards the future.
In: Springer eBooksSummary: This book gives a synthesis of the state of the art in artificial intelligence in astronomy and astrophysics, presents its current applications and points out directions of future work. The individual chapters report on the application of artificial intelligence techniques for large astronomical surveys, for processing cosmic ray data, for facilitating data reduction using image processing systems, for telescope scheduling, for observatory ground support operations, for observation proposal preparation assistance, and for scientific applications such as stellar spectral and galaxy morphology classification. The new field of connectionism (neural networks) is also surveyed. The book is designed to be self-contained: a glossary of terms used in this area is provided and an index of terms, acronyms and proper names completes the book.
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Artificial intelligence applications for Hubble Space Telescope operations -- Knowledge based telescope scheduling -- Survey work with automated data analysis -- Distributed point-pattern matching -- Decision problems in the search for periodicities in gamma-ray astronomy. How can A.I. help? -- Classification and knowledge -- WOLF — A computer expert system for sunspot classification and solar flare prediction -- Knowledge based classification of galaxies -- Classification of IUE spectra: A rule based approach -- Representation of knowledge using Fuzzy set theory -- An approach to heuristic exploitation of astronomers' knowledge in automatic interpretation of optical pictures -- Connectionism and neural networks -- Applications of AI in astronomy: A view towards the future.

This book gives a synthesis of the state of the art in artificial intelligence in astronomy and astrophysics, presents its current applications and points out directions of future work. The individual chapters report on the application of artificial intelligence techniques for large astronomical surveys, for processing cosmic ray data, for facilitating data reduction using image processing systems, for telescope scheduling, for observatory ground support operations, for observation proposal preparation assistance, and for scientific applications such as stellar spectral and galaxy morphology classification. The new field of connectionism (neural networks) is also surveyed. The book is designed to be self-contained: a glossary of terms used in this area is provided and an index of terms, acronyms and proper names completes the book.

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