Advantages and Pitfalls of Pattern Recognition: Selected Cases in Geophysics

by Horst Langer, Susanna Falsaperla, Conny Hammer

Overview

Advantages and Pitfalls of Pattern Recognition presents various methods of pattern recognition and classification, useful to geophysicists, geochemists, geologists, geographers, data analysts, and educators and students of geosciences. Scientific and technological progress has dramatically improved the knowledge of our planet with huge amounts of digital data available in various fields of Earth Sciences, such as geology, geophysics, and geography. This has led to a new perspective of data analysis, requiring specific techniques that take several features into consideration rather than single parameters. Pattern recognition techniques offer a suitable key for processing and extracting useful information from the data of multivariate analysis. This book explores both supervised and unsupervised pattern recognition techniques, while providing insight into their application.

Product Details

ISBN-13:	9780128118429
Publisher:	Elsevier Science
Publication date:	11/20/2019
Series:	Computational Geophysics , #3
Pages:	350
Product dimensions:	7.50(w) x 9.25(h) x (d)

About the Author

Horst Langer has developed methods for automatic alert systems and early warning on Mount Etna as well as tools that are routinely operated in the monitoring room of the institute and are part of the alert system for Civil Protection. Aside from his documented experience in the application of various pattern recognition techniques, he has also published computer programs for pattern recognition.

Susanna Falsaperla has a long experience in the application of pattern recognition techniques and was among the first seismologists to apply automatic classification to seismic signals on volcanoes. She has made extensive use of pattern recognition in volcanology to relate multidisciplinary data to volcanic unrest and eruptive activity.

Conny Hammer has worked on automatic classification of seismic signals in continuous data streams and has introduced novel concepts and tools into the seismological community from fields of machine learning (e.g., speech processing). Her automatic recognition tools are currently implemented in daily observatory routines. Besides automatic event detection, she has focused on the application of machine learning tools in seismic site characterization.

Table of Contents

Part I: From Data to Methods1. Patterns, Objects, and Features2. Supervised Learning3. Unsupervised Learning

Part II: Example Applications4. Applications with Supervised Learning5.. Applications with Unsupervised Learning

Part III: A Posteriori Analysis6. What is a Failure? A-posteriori Analyses - Advantages and Pitfalls of Pattern Recognition Techniques7. Software Manuals

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From the Publisher

A guide for identifying strategies for preparing multivariate data, selecting features, and reading and interpreting output in a variety of geophysical applications