rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Computational neural networks for geophysical data processing
  name:
    name part: Poulton, Mary M.
  name:
    name part: Knovel (Firm)
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: ne
    date issued: 2001
    edition: 1st ed.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (xiii, 335 pages) : illustrations.
  abstract: This book was primarily written for an audience that has heard about neural networks or has had some experience with the algorithms, but would like to gain a deeper understanding of the fundamental material. For those that already have a solid grasp of how to create a neural network application, this work can provide a wide range of examples of nuances in network design, data set design, testing strategy, and error analysis. Computational, rather than artificial, modifiers are used for neural networks in this book to make a distinction between networks that are implemented in hardware and those that are implemented in software. The term artificial neural network covers any implementation that is inorganic and is the most general term. Computational neural networks are only implemented in software but represent the vast majority of applications. While this book cannot provide a blue print for every conceivable geophysics application, it does outline a basic approach that has been used successfully.
  table of contents: Front Cover; Computational Neural Networks for Geophysical Data Processing; Copyright Page; Table of Contents; Preface; Contributing Authors; Part I: Introduction to Computational Neural Networks; Chapter 1. A Brief History; Chapter 2. Biological Versus Computational Neural Networks; Chapter 3. Multi-Layer Perceptrons and Back-Propagation Learning; Chapter 4. Design of Training and Testing Sets; Chapter 5. Alternative Architectures and Learning Rules; Chapter 6. Software and Other Resources; Part II: Seismic Data Processing; Chapter 7. Seismic Interpretation and Processing Applications.
  table of contents: Chapter 8. Rock Mass and Reservoir CharacterizationChapter 9. Identifying Seismic Crew Noise; Chapter 10. Self-Organizing Map (SOM) Network for Tracking Horizons and Classifying Seismic Traces; Chapter 11. Permeability Estimation with an RBF Network and Levenberg-Marquardt Learning; Chapter 12. Caianiello Neural Network Method for Geophysical Inverse Problems; Part III: Non-Seismic Applications; Chapter 13. Non-Seismic A.
  note: edited by Mary M. Poulton.
  note: Electronic resource.
  note: Includes bibliographical references and indexes.
  subject:
    topic: Prospecting
    topic: Geophysical methods
    topic: Data processing
  subject:
    topic: Neural networks (Computer science)
  subject:
    topic: TECHNOLOGY & ENGINEERING
    topic: Mining
  subject:
    topic: Neural networks (Computer science)
  subject:
    topic: Prospecting
    topic: Geophysical methods
    topic: Data processing
  subject:
    topic: Prospecting
    topic: Geophysical methods
    topic: Data processing. Neural networks (Computer science)
  subject:
    topic: Data processing
  subject:
    topic: Geophysical methods
  subject:
    topic: Neural networks (Computer science)
  subject:
    topic: Prospecting
  classification: TN269 .C59 2001eb
  classification: 622/.15/0285632
  related item:
    title info:
      title: Computational neural networks for geophysical data processing
    origin info:
      publisher: Amsterdam ; New York : Pergamon, 2001
      edition: 1st ed.
    identifier: (DLC) 2001033815
    identifier: (OCoLC)46992095
  related item:
    title info:
      title: Handbook of geophysical exploration. v. 30
      part number: Section I
      part name: Seismic exploration
  identifier: 0080439861
  identifier: 9780080439860
  identifier: 9780080529653
  identifier: 0080529658
  identifier: 1281038091
  identifier: 9781281038098
  identifier: 00991439
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: WAU
    record creation date: 080114
    record change date: 20260609152604.7
    record identifier: in00003832142
    language of cataloging:
      language term: eng