A learning vector quantization neural network model for the classification of industrial construction projects
In several key functional areas of contemporary engineering and management science, neural networks have steadily been gaining recognition as robust and reliable tools for classification problems. This paper describes a new application of the learning vector quantization neural network: the classification of the degree of modularization appropriate for the construction of an industrial facility. This neural network uses variables related to plant location, labor issues, organizational issues, plant characteristics, project risks, and environmental issues as inputs to perform the classification. The neural network training and performance evaluation is also discussed.
Year of publication: |
1997
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Authors: | Gupta, V. K. ; Chen, J. G. ; Murtaza, M. B. |
Published in: |
Omega. - Elsevier, ISSN 0305-0483. - Vol. 25.1997, 6, p. 715-727
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Publisher: |
Elsevier |
Keywords: | neural networks construction industry application classification decision making learning vector quantization |
Saved in:
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