Computational neural networks for geophysical data processing

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, thi...

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Bibliographic Details
Other Authors: Poulton, Mary M.
Format: eBook
Language: English
Published: Amsterdam ; New York : Pergamon, 2001.
Edition: 1st ed.
Series: Handbook of geophysical exploration. Seismic exploration ; v. 30.
Subjects:
Prospecting > Geophysical methods > Data processing.
Neural networks (Computer science)
elektronické knihy
electronic books
ISBN: 0080439861
9780080439860
9780080529653
0080529658
1281038091
9781281038098
Physical Description: 1 online resource (xiii, 335 pages) : illustrations

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Table of contents

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245 0 0 |a Computational neural networks for geophysical data processing /  |c edited by Mary M. Poulton. 
250 |a 1st ed. 
260 |a Amsterdam ;  |a New York :  |b Pergamon,  |c 2001. 
300 |a 1 online resource (xiii, 335 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Seismic exploration,  |x 0950-1401 ;  |v v. 30 
504 |a Includes bibliographical references and indexes. 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a 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. 
505 0 |a 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. 
505 8 |a 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. 
590 |a Knovel  |b Knovel (All titles) 
650 0 |a Prospecting  |x Geophysical methods  |x Data processing. 
650 0 |a Neural networks (Computer science) 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
700 1 |a Poulton, Mary M. 
776 0 8 |i Print version:  |t Computational neural networks for geophysical data processing.  |b 1st ed.  |d Amsterdam ; New York : Pergamon, 2001  |z 0080439861  |z 9780080439860  |w (DLC) 2001033815  |w (OCoLC)46992095 
830 0 |a Handbook of geophysical exploration.  |n Section I,  |p Seismic exploration ;  |v v. 30. 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpCNNGDP0K/computational-neural-networks?kpromoter=marc  |y Full text 

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