A data mining approach to dynamic multiple responses in Taguchi experimental design

Expert Systems with Applications

Volumn 35, Issue 3, 2008, Pages 1095-1103

  Chang, Hsu Hwa ^a  

^a NATIONAL TAIPEI UNIVERSITY OF BUSINESS   (Taiwan)

Author keywords

Artificial neural networks; Desirability functions; Dynamic multiple responses; Simulated annealing; Taguchi experimental design

Indexed keywords

ADMINISTRATIVE DATA PROCESSING; ALGORITHMS; ANNEALING; ARCHITECTURAL DESIGN; ARTIFICIAL INTELLIGENCE; BACKPROPAGATION; BOOLEAN FUNCTIONS; COMPUTER NETWORKS; DATA MINING; DECISION SUPPORT SYSTEMS; DYNAMICAL SYSTEMS; DYNAMICS; EVOLUTIONARY ALGORITHMS; FUNCTION EVALUATION; FUNCTIONS; INFORMATION MANAGEMENT; INTEGER PROGRAMMING; KNOWLEDGE MANAGEMENT; MANAGEMENT INFORMATION SYSTEMS; MATHEMATICAL MODELS; MECHANICS; METROPOLITAN AREA NETWORKS; MINING; NETWORK PROTOCOLS; NEURAL NETWORKS; PARAMETER ESTIMATION; PRODUCT DESIGN; SCHEDULING ALGORITHMS; SEARCH ENGINES;

(001) PARAMETER; APPLIED (CO); ARTIFICIAL NEURAL NETWORKS (ANN); CONTINUOUS CONTROL; DESIRABILITY FUNCTIONS; DYNAMIC PARAMETERS; ELSEVIER (CO); MULTIPLE RESPONSES; NOISE FACTORS; PERFORMANCE MEASURE (PF); PRODUCT COMPLEXITY; PRODUCTION TIME; RESPONSE FUNCTIONS; ROBUST DESIGNS; SA ALGORITHMS; SIMULATED ANNEALING (SA) ALGORITHMS; TAGUCHI EXPERIMENTAL DESIGN; UPPER AND LOWER BOUNDS;

SIMULATED ANNEALING;

EID: 45149085865     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2007.08.005     Document Type: Article

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