Recognition of control chart concurrent patterns using a neural network approach

DOI10.1080/002075499190987zbMath0949.90526OpenAlexW2125290375MaRDI QIDQ4497010

J. D. T. Tannock, Ruey-Shiang Guh

Publication date: 21 August 2000

Published in: International Journal of Production Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/002075499190987

Mathematics Subject Classification ID

Production models (90B30)

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A hybrid neural network–genetic algorithm approach for permutation flow shop scheduling ⋮ Applying two-stage neural network based classifiers to the identification of mixture control chart patterns for an SPC-EPC process ⋮ Real-time recognition of control chart patterns in autocorrelated processes using a learning vector quantization network-based approach ⋮ Machine-part cell formation in group technology using a modified ART1 method ⋮ Adaptive resonance theory-based neural algorithms for manufacturing process quality control ⋮ On-line identification of control chart patterns using self-organizing approaches ⋮ Extraction and organization of statistical distribution functions for simulation of variations and patterns in the variability control charts

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