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Volumn 33, Issue 9, 1995, Pages 2395-2413

A variable-parameter unsupervised learning clustering neural network approach with application to machine-part group formation

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Indexed keywords


EID: 84952529136     PISSN: 00207543     EISSN: 1366588X     Source Type: Journal    
DOI: 10.1080/00207549508904823     Document Type: Article
Times cited : (24)

References (35)
  • 2
    • 0021776661 scopus 로고
    • A massively parallel architectur for a selforganizing neural pattern recognition machine
    • CARPENTER, G., and GROSSBERG, S., 1987, A massively parallel architectur for a selforganizing neural pattern recognition machine. Computer Vision, Graphics and image Processing, 37, 54-115.
    • (1987) Computer Vision, Graphics and Image Processing , vol.37 , pp. 54-115
    • Carpenter, G.1    Grossberg, S.2
  • 3
    • 84973857317 scopus 로고
    • ART2: Self-organization of stable category recognition codes for analog input patterns
    • CARPENTER, G., and GROSSBERG, S., 1987, ART2: Self-organization of stable category recognition codes for analog input patterns. Applied Optics, 26, 4919-4946.
    • (1987) Applied Optics , vol.26 , pp. 4919-4946
    • Carpenter, G.1    Grossberg, S.2
  • 4
    • 0020388157 scopus 로고
    • Direct clustering algorithm for group formation in cellular manufacture
    • CHAN, H. M., and MILNER, D. A., 1982, Direct clustering algorithm for group formation in cellular manufacture. Journal of Manufacturing Systems, 9, 65-75.
    • (1982) Journal of Manufacturing Systems , vol.9 , pp. 65-75
    • Chan, H.M.1    Milner, D.A.2
  • 8
    • 0017120827 scopus 로고
    • Adaptive pattern classification and universal recording I: Parallel development and coding of neural feature detectors
    • GROSSBERG, S., 1976, Adaptive pattern classification and universal recording I: parallel development and coding of neural feature detectors. Biological Cybernetics, 23, 121-134.
    • (1976) Biological Cybernetics , vol.23 , pp. 121-134
    • Grossberg, S.1
  • 9
    • 5244352553 scopus 로고
    • Competitive learning: From interactive activation to adaptive resonance
    • GROSSBERG, S., 1987, Competitive learning: from interactive activation to adaptive resonance. Cognitive Science, 11, 23-63.
    • (1987) Cognitive Science , vol.11 , pp. 23-63
    • Grossberg, S.1
  • 10
    • 0025247622 scopus 로고
    • An efficient heuristic in manufacturing cell formation for group technology application
    • HARHALAKIS et al., 1990a, An efficient heuristic in manufacturing cell formation for group technology application. International Journal of Production Research, 28, 185-198.
    • (1990) International Journal of Production Research , vol.28 , pp. 185-198
    • Harhalakis1
  • 11
    • 0000509815 scopus 로고
    • Manufacturing Cell Design Using Simulated Annealing: An Industrial Application
    • HARHALAKIS et al., 1990b, Manufacturing Cell Design Using Simulated Annealing: An Industrial Application. Journal of Intelligent Manufacturing, 1, 185-191.
    • (1990) Journal of Intelligent Manufacturing , vol.1 , pp. 185-191
    • Harhalakis1
  • 12
    • 0026077034 scopus 로고
    • Manufacturing Cells and Part Families: Generalization of the GP Method
    • HARHALAKIS et al., 1991, Manufacturing Cells and Part Families: Generalization of the GP Method. Information and Decision Technologies, 17, 51-61.
    • (1991) Information and Decision Technologies , vol.17 , pp. 51-61
    • Harhalakis1
  • 13
    • 0021835689 scopus 로고
    • Neural computation of decision in optimization problems
    • HOPFJELD, J. J., and TANK, D. W., 1985, Neural computation of decision in optimization problems. Biological Cybernetics, 52, 141-152.
    • (1985) Biological Cybernetics , vol.52 , pp. 141-152
    • Hopfjeld, J.J.1    Tank, D.W.2
  • 14
    • 49149149610 scopus 로고
    • Machine-component group formation in group technology
    • King, J. R., 1980a, Machine-component group formation in group technology. OMEGA, 8, 193-199.
    • (1980) OMEGA , vol.8 , pp. 193-199
    • King, J.R.1
  • 15
    • 0018991743 scopus 로고
    • Machine-component grouping in production flow analysis: An approach using a rank order clustering algorithm
    • KING, J. R., 1980b, Machine-component grouping in production flow analysis: an approach using a rank order clustering algorithm. International Journal of Production Research, 18, 213-232.
    • (1980) International Journal of Production Research , vol.18 , pp. 213-232
    • King, J.R.1
  • 16
    • 84952494480 scopus 로고
    • Machine-component group formation in group technology: Review and extension
    • KING, J. R., and NAKORNCHAJ, V., 1982, Machine-component group formation in group technology: review and extension. International Journal of Production Research, 20, 117-133.
    • (1982) International Journal of Production Research , vol.20 , pp. 117-133
    • King, J.R.1    Nakornchaj, V.2
  • 18
    • 0023855839 scopus 로고
    • An Introduction to Neural Computing
    • KOHONEN, T., 1988, An Introduction to Neural Computing. Neural Networks, I, 3-16.
    • (1988) Neural Networks , vol.1 , pp. 3-16
    • Kohonen, T.1
  • 21
    • 0024771475 scopus 로고
    • Pattern classification using neural networks
    • November
    • LIPPMANN, R. P., 1989, Pattern classification using neural networks. IEEE Communications Magazine, November, 47-64.
    • (1989) IEEE Communications Magazine , pp. 47-64
    • Lippmann, R.P.1
  • 23
    • 0023868193 scopus 로고
    • A decision support system and a heuristic interactive approach for solving discrete multiple criteria problems
    • MALAKOOTI, B. 1988, A decision support system and a heuristic interactive approach for solving discrete multiple criteria problems. IEEE Transactions On Systems Man and Cybernetics, 18, 273-285.
    • (1988) IEEE Transactions on Systems Man and Cybernetics , vol.18 , pp. 273-285
    • Malakooti, B.1
  • 24
    • 0024631561 scopus 로고
    • Theories and an exact interactive paired comparison approach for discrete multiple criteria problems
    • MALAKOOTI, B., 1989, Theories and an exact interactive paired comparison approach for discrete multiple criteria problems. IEEE Transactions on Systems, Man and Cybernetics, 19(2), 365-378.
    • (1989) IEEE Transactions on Systems, Man and Cybernetics , vol.19 , Issue.2 , pp. 365-378
    • Malakooti, B.1
  • 25
    • 0001340484 scopus 로고
    • Assembly line balancing with buffers by multiple criteria optimization
    • MALAKOOTI, B., 1994, Assembly line balancing with buffers by multiple criteria optimization. International Journal of Production Research, 32(9), 2159-2178.
    • (1994) International Journal of Production Research , vol.32 , Issue.9 , pp. 2159-2178
    • Malakooti, B.1
  • 26
    • 0024736321 scopus 로고
    • An interactive multiple criteria approach for parameter selection in metal cutting
    • MALAKOOTI, B., and DEVIPRASAD, J., 1989, An interactive multiple criteria approach for parameter selection in metal cutting. Operations Research, 37(5), 805-818.
    • (1989) Operations Research , vol.37 , Issue.5 , pp. 805-818
    • Malakooti, B.1    Deviprasad, J.2
  • 27
    • 84952547333 scopus 로고
    • An adaptive feedforward artificial neural network with application to multiple criteria decision making
    • MALAKOOTI, B., and ZHOU, Y., 1995a, An adaptive feedforward artificial neural network with application to multiple criteria decision making. Management Science, 39, (in press).
    • (1995) Management Science , vol.39
    • Malakooti, B.1    Zhou, Y.2
  • 28
    • 0029253618 scopus 로고
    • In-process regressions and adaptive neural networks for monitoring and supervising machining operations
    • MALAKOOTI, B., ZHOU, Y., and TANDLER, E. C., 1995b, In-process regressions and adaptive neural networks for monitoring and supervising machining operations, Journal of Intelligent Manufacturing, 5, (in press).
    • (1995) Journal of Intelligent Manufacturing , vol.5
    • Malakooti, B.1    Zhou, Y.2    Tandler, E.C.3
  • 29
    • 30244478671 scopus 로고
    • Opinions aggregation
    • Janssen, J., Marco torchi no, P., and Proth, I. M. (eds) (North Holland: Elsevier
    • MICHAUD, P., 1983, Opinions aggregation. In New Trends in Data Analysis and Applications, Janssen, J., Marco torchi no, P., and Proth, I. M. (eds) (North Holland: Elsevier).
    • (1983) New Trends in Data Analysis and Applications
    • Michaud, P.1
  • 30
    • 0002656190 scopus 로고
    • Feature discovery by competitive learning
    • RUMELHART, D. E., and ZIPSER, D., 1985, Feature discovery by competitive learning. Cognitive Science, 9, 75-112.
    • (1985) Cognitive Science , vol.9 , pp. 75-112
    • Rumelhart, D.E.1    Zipser, D.2
  • 31
    • 0022471098 scopus 로고
    • Learning internal representations by back-propagating errors
    • RUMELHART, D. E., HINTON, G., and WILLIAMS, R., 1986. Learning internal representations by back-propagating errors. Nature, 323, 533-536.
    • (1986) Nature , vol.323 , pp. 533-536
    • Rumelhart, D.E.1    Hinton, G.2    Williams, R.3
  • 32
    • 0024883243 scopus 로고
    • Optimal unsupervised learning in a single-layer linear feedforward neural network
    • SANGER, T., 1989, Optimal unsupervised learning in a single-layer linear feedforward neural network. Neural Networks, 2, 459-473.
    • (1989) Neural Networks , vol.2 , pp. 459-473
    • Sanger, T.1
  • 34
    • 0026821843 scopus 로고
    • A feedforward neural network for multiple criteria decision making
    • WANG, J., and MALAKOOTI, B., 1992, A feedforward neural network for multiple criteria decision making, Computers and Operations Research, 19(2), 151-167.
    • (1992) Computers and Operations Research , vol.19 , Issue.2 , pp. 151-167
    • Wang, J.1    Malakooti, B.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.