A nonlinear support vector machine‐based feature selection approach for fault detection and diagnosis: Application to the Tennessee Eastman process-Reference-Cited by-同舟云学术

A nonlinear support vector machine‐based feature selection approach for fault detection and diagnosis: Application to the Tennessee Eastman process

Author:

Onel Melis¹²,Kieslich Chris A.¹²³,Pistikopoulos Efstratios N.¹²^ORCID

Affiliation:

1. Artie McFerrin Dept. of Chemical Engineering Texas A&M University College Station, Texas 77843

2. Texas A&M Energy Institute Texas A&M University College Station, Texas 77843

3. Coulter Dept. of Biomedical Engineering Georgia Institute of Technology Atlanta Georgia

Funder

National Institutes of Health

National Science Foundation

Publisher

Wiley

Subject

General Chemical Engineering,Environmental Engineering,Biotechnology

Link

Reference54 articles.

3. Smart manufacturing and energy systems;Edgar TF;Comput Chem Eng.,2017

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