Unsupervised process fault detection with random forests

Industrial and Engineering Chemistry Research

Volumn 49, Issue 19, 2010, Pages 9184-9194

  Auret, Lidia ^a   Aldrich, Chris ^a  

^a STELLENBOSCH UNIVERSITY   (South Africa)

Author keywords

[No Author keywords available]

Indexed keywords

ADVANCED DIAGNOSTIC SYSTEMS; BINARY DECISION TREES; CLASSIFICATION AND REGRESSION TREE; COMPLEX SYSTEMS; DATA-DRIVEN; DIMENSIONAL SPACES; ENVIRONMENTALLY RESPONSIBLE; MINERAL PROCESSING PLANTS; MODEL RESPONSE; MONITORING TECHNOLOGIES; NONLINEAR PROCESS; PROCESS FAULT DETECTION; RANDOM FORESTS; RAPID DEVELOPMENT; REAL-WORLD; UNSTEADY STATE;

BINARY TREES; FAULT DETECTION; PROCESS MONITORING;

DECISION TREES;

EID: 77957600831     PISSN: 08885885     EISSN: 15205045     Source Type: Journal    
DOI: 10.1021/ie901975c     Document Type: Article

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