A learning vector quantization neural network model for the classification of industrial construction projects

被引:7
作者
Gupta, VK
Chen, JG
Murtaza, MB
机构
[1] UNIV HOUSTON,HOUSTON,TX
[2] FLORIDA A&M UNIV,TALLAHASSEE,FL 32307
来源
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE | 1997年 / 25卷 / 06期
关键词
neural networks; construction industry; application; classification; decision making; learning vector quantization;
D O I
10.1016/S0305-0483(97)00025-X
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
In several key functional areas of contemporary engineering and management science, neural networks have steadily been gaining recognition as robust and reliable toots 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. (C) 1997 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:715 / 727
页数:13
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