Least squares support vector machine (LS-SVM)-based chiller fault diagnosis using fault indicative features

Title
Least squares support vector machine (LS-SVM)-based chiller fault diagnosis using fault indicative features
Authors
Keywords
Fault detection and diagnosis, Least squares support vector machine, Optimization, Chiller, Refrigeration
Journal
APPLIED THERMAL ENGINEERING
Volume 154, Issue -, Pages 540-547
Publisher
Elsevier BV
Online
2019-03-24
DOI
10.1016/j.applthermaleng.2019.03.111

Ask authors/readers for more resources

Reprint

Contact the author

Create your own webinar

Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.

Create Now

Ask a Question. Answer a Question.

Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.

Get Started