A novel optimized SVM algorithm based on PSO with saturation and mixed time-delays for classification of oil pipeline leak detection

A novel optimized SVM algorithm based on PSO with saturation and mixed time-delays for classification of oil pipeline leak detection

In this paper, a novel particle swarm optimization (PSO) algorithm is proposed in order to improve the accuracy of the traditional support vector machine (SVM) approaches with applications in analyzing data of oil pipeline leak detection. In the proposed saturated and mix-delayed particle swarm opti...

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Bibliographic Details
Main Authors: Chuang Wang, Yong Zhang, Jinbo Song, Qingqiang Liu, Hongli Dong
Format: Article
Language:English
Published: Taylor & Francis Group 2019-01-01
Series:Systems Science & Control Engineering
Subjects:
Oil pipeline leak detection
classification
particle swarm optimization
support vector machine
saturation
mixed time-delays
Online Access:http://dx.doi.org/10.1080/21642583.2019.1573386

Internet

http://dx.doi.org/10.1080/21642583.2019.1573386

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