Identification of the dynamic operating envelope of HCCI engines using class imbalance learning

IEEE Transactions on Neural Networks and Learning Systems

Volumn 26, Issue 1, 2015, Pages 98-112

  Janakiraman, Vijay Manikandan ^a,b   Nguyen, Xuanlong ^a   Sterniak, Jeff ^c   Assanis, Dennis ^d  

^a UNIVERSITY OF MICHIGAN   (United States)

^b NASA AMES RESEARCH CENTER   (United States)

^c ROBERT BOSCH GMBH   (Germany)

^d STONY BROOK UNIVERSITY   (United States)

Author keywords

Class imbalance learning; dynamic classification; engine control; engine diagnostics; extreme learning machine; homogeneous charge compression ignition; misfire prediction; operating envelope model; support vector machine; system identification.

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMBUSTION KNOCK; CONTROLLERS; ENGINE CYLINDERS; FUEL ECONOMY; IDENTIFICATION (CONTROL SYSTEMS); IGNITION; KNOWLEDGE ACQUISITION; SUPPORT VECTOR MACHINES;

CLASS IMBALANCE LEARNING; DYNAMIC CLASSIFICATION; ENGINE CONTROL; ENGINE DIAGNOSTICS; ENVELOPE MODELS; EXTREME LEARNING MACHINE; HOMOGENEOUS CHARGE COMPRESSION IGNITION;

ENGINES;

EID: 84919597328     PISSN: 2162237X     EISSN: 21622388     Source Type: Journal    
DOI: 10.1109/TNNLS.2014.2311466     Document Type: Article

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