A Support Vector Machine Model for Pipe Crack Size Classification: Reseach on SVM


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.

Publisher‏:‎VDM Verlag Dr. Müller (Sept. 15 2010)
Language‏:‎English
Paperback‏:‎96 pages
ISBN-10‏:‎363929405X
ISBN-13‏:‎978-3639294057
Item weight‏:‎150 g
Dimensions‏:‎15.01 x 0.56 x 22 cm
Product information :

Product A Support Vector Machine Model for Pipe Crack Size Classification: Reseach on SVM
price Sell$77.53
keyword search:pipa da crack
product_asin363929405X

>> Price sell: $77.53
(as of Oct 23,2021 05:28:02 UTC) — [Details]

>>Click here to get A Support Vector Machine Model for Pipe Crack Size Classification: Reseach on SVM at discounted price while it’s still available…<<

Product hashtags: #Support #Vector #Machine #Model #Pipe #Crack #Size #Classification #Reseach #SVM :

Leave a Reply

Your email address will not be published.