Leak detection of pipeline: An integrated approach of rough set theory and artificial bee colony trained SVM

Author:

Mandal Santosh Kumar,Chan Felix T.S.,Tiwari M.K.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference38 articles.

1. Least squares twin support vector machines;Arun;Expert Systems with Applications,2009

2. Leak detection in liquefied gas pipelines by artificial neural networks;Belsito;AICHE Journal,1998

3. Forecasting systems reliability based on support vector regression with genetic algorithms;Chen;Reliability Engineering and System Safety,2007

4. Chen, H., Ye, H., Lv, C. and Su, H. (2004). Application of support vector machine learning to leak detection and location in pipelines. In IEEE instrumentation and measurement technology conference, Como, Italy.

5. Chouchoulas, A. (1999). A Rough Set Approach to Text Classification. Msc. Thesis. School of artificial intelligence, University of Edinburgh, United Kingdom.

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