عنوان

Computational neural networks for geophysical data processing /

شابک

0080439861

شابک

0080529658

شابک

1281038091

شابک

9780080439860

شابک

9780080529653

شابک

9781281038098

شماره

b710371

عنوان اصلي

Computational neural networks for geophysical data processing /

نام عام مواد

[Book]

نام نخستين پديدآور

edited by Mary M. Poulton.

وضعيت ويراست

1st ed.

محل نشرو پخش و غیره

New York :

نام ناشر، پخش کننده و غيره

Pergamon,

تاریخ نشرو بخش و غیره

2001.

نام خاص و کميت اثر

1 online resource (xiii, 335 pages) :

ساير جزييات

illustrations.

عنوان فروست

Seismic exploration,

مشخصه جلد

v. 30

شاپا ي ISSN فروست

0950-1401 ;

متن يادداشت

Includes bibliographical references and indexes.

متن يادداشت

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.

متن يادداشت

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.

بدون عنوان

0

بدون عنوان

8

متن يادداشت

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.

منبع سفارش / آدرس اشتراک

00991439

عنوان

Computational neural networks for geophysical data processing.

شماره استاندارد بين المللي کتاب و موسيقي

9780080439860

موضوع مستند نشده

Neural networks (Computer science)

موضوع مستند نشده

Prospecting-- Geophysical methods-- Data processing.

موضوع مستند نشده

Neural networks (Computer science)

موضوع مستند نشده

Prospecting-- Geophysical methods-- Data processing.

موضوع مستند نشده

TECHNOLOGY & ENGINEERING-- Mining.

موضوع مستند نشده

QC

موضوع مستند نشده

RBG

موضوع مستند نشده

TEC-- 026000

شماره

ويراست

شماره رده

نشانه اثر

مستند نام اشخاص تاييد نشده

Poulton, Mary M.

تاريخ عمليات

20201208010734.0

قواعد فهرست نويسي ( بخش توصيفي )

pn

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y