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Support Vector Machine Model for Pipe Crack Size Classification

Language EnglishEnglish
Book Paperback
Book Support Vector Machine Model for Pipe Crack Size Classification Chuxiong Miao
Libristo code: 06836479
Publishers VDM Verlag, September 2010
The classification of pipe crack size from its pulse- echo ultrasonic signal is a difficult task but... Full description
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The classification of pipe crack size from its pulse- echo ultrasonic signal is a difficult task but greatly significant for defect evaluation in pipe testing and the maintenance strategy making. In this book, we use Support Vector Machines (SVM) to classify the pipe crack into correct categories, large size or small size, with the ultrasonic signal data. In order to acquire an optimal input data set, we first select the features from the time and frequency domain on the ultrasonic data. Then a combined method, Sequential Backward Selection (SBS) and Sequential Forward Selection (SFS), is used for features reduction. These two steps are referred as data preprocessing in this book. To build SVM classifier, parameter selection is critical. In this book, a Kernel Fisher Discriminant Ratio (KFD Ratio) is proposed for speeding the parameter selection of the SVM classifier. As an indicator, KFD Ratio can greatly shorten computation time for finding the best parameters. To further improve the performance of the SVM classifier in terms of classification accuracy, a data dependent kernel is adopted for creating a more effective one.

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About the book

Full name Support Vector Machine Model for Pipe Crack Size Classification
Language English
Binding Book - Paperback
Date of issue 2010
Number of pages 96
EAN 9783639294057
ISBN 363929405X
Libristo code 06836479
Publishers VDM Verlag
Weight 150
Dimensions 152 x 229 x 6
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