Transition process modeling and monitoring based on dynamic ensemble clustering and multiclass support vector data description

Industrial and Engineering Chemistry Research

Volumn 50, Issue 24, 2011, Pages 13969-13983

  Zhu, Zhibo ^a,b   Song, Zhihuan ^a   Palazoglu, Ahmet ^b  

^a STATE KEY LABORATORY OF INDUSTRIAL CONTROL TECHNOLOGY   (China)

^b University of California Davis   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ABNORMAL OPERATION; COMPONENT ANALYSIS; CRITICAL ACTIVITIES; DIMENSION REDUCTION; ENSEMBLE CLUSTERING; FAULTY OPERATIONS; MONITORING AND MANAGEMENT; MULTI-CLASS; NON-GAUSSIAN; NONSTATIONARY; ON DYNAMICS; SUPPORT VECTOR DATA DESCRIPTION; SYSTEMATIC FRAMEWORK; TENNESSEE EASTMAN; TIME-SERIES DATA; TRANSITION PROCESS; TRANSITION STATE;

BENCHMARKING; CHEMICAL OPERATIONS; CHEMICAL PLANTS; CLUSTER ANALYSIS; DATA DESCRIPTION; INDEPENDENT COMPONENT ANALYSIS; PROCESS MONITORING; TIME SERIES; TIME SERIES ANALYSIS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 83655192514     PISSN: 08885885     EISSN: 15205045     Source Type: Journal    
DOI: 10.1021/ie201792r     Document Type: Article

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