Signal Classification for Pipeline Security Threat Event Based on Optimized Support Vector Machine

E-ISSN： 1662-9795|2016|693|1428-1435

ISSN： 1013-9826

Source： Key Engineering Materials, Vol.2016, Iss.693, 2016-06, pp. : 1428-1435

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Abstract

Related content

Classification of acoustic emission sources produced by carbon/epoxy composite based on support vector machine

IOP Conference Series: Materials Science and Engineering, Vol. 87, Iss. 1, 2015-07 ,pp. : 8-13

IOP Publishing

Access to resources Recommend Favorite

A Fault Alarm and Diagnosis Method Based on Sensitive Parameters and Support Vector Machine

IOP Conference Series: Materials Science and Engineering, Vol. 90, Iss. 1, 2015-08 ,pp. : 754-763

IOP Publishing

Access to resources Recommend Favorite

Optimization of Milling Parameters for Titanium Alloys Based on Support Vector Machine (Machine Learning) and Ant Colony Optimization Algorithm

Key Engineering Materials, Vol. 2018, Iss. 770, 2018-07 ,pp. : 262-267

Trans Tech Publications

Access to resources Recommend Favorite

Carbon dioxide emission prediction using support vector machine

IOP Conference Series: Materials Science and Engineering, Vol. 114, Iss. 1, 2016-02 ,pp. : 1284-1291

IOP Publishing

Access to resources Recommend Favorite

Passive Sensing of Sensorized Composite Panels: Support Vector Machine

Key Engineering Materials, Vol. 2016, Iss. 713, 2016-11 ,pp. : 199-202

Trans Tech Publications

Access to resources Recommend Favorite