Effective recognition of control chart patterns in autocorrelated data using a support vector machine based approach

Computers and Industrial Engineering

Volumn 61, Issue 4, 2011, Pages 1123-1134

  Lin, Shih Yen ^a   Guh, Ruey Shiang ^b   Shiue, Yeou Ren ^c  

^a NATIONAL CHI NAN UNIVERSITY   (Taiwan)

^b NATIONAL FORMOSA UNIVERSITY   (Taiwan)

^c HUAFAN UNIVERSITY   (Taiwan)

Author keywords

Artificial neural networks; Autocorrelated data; Control charts; Pattern recognition; Statistical process control; Support vector machines

Indexed keywords

ASSIGNABLE CAUSE; AUTOCORRELATED DATA; BACKGROUND NOISE; BACKPROPAGATION NETWORK; CONTROL CHART PATTERN; CONTROL CHARTS; CRITICAL ISSUES; EMPIRICAL COMPARISON; EMPIRICAL RISK MINIMIZATION; LEARNING VECTOR QUANTIZATION NETWORKS; MACHINE LEARNING TECHNIQUES; MISCLASSIFICATIONS; MODEL-BASED OPC; PROCESS DATA; REAL TIME RECOGNITION; RECOGNITION ACCURACY; RECOGNITION MODELS; RECOGNITION SPEED; RESEARCH FIELDS; STATISTICAL PROCESS; STRUCTURAL RISK MINIMIZATION; SUPPORT VECTOR; TRAINING DATA; TRAINING EXAMPLE;

FACE RECOGNITION; FLOWCHARTING; NEURAL NETWORKS; QUALITY CONTROL; SUPPORT VECTOR MACHINES; VECTOR QUANTIZATION; VECTORS;

STATISTICAL PROCESS CONTROL;

EID: 80054955956     PISSN: 03608352     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cie.2011.06.025     Document Type: Article

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