Development of a Cost Predicting Model for Maintenance of University Buildings

被引:0
|
作者
Li, Chang-Sian [1 ]
Guo, Sy-Jye [1 ]
机构
[1] Natl Taiwan Univ, Dept Civil Engn, Taipei 10764, Taiwan
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
If a university building's performance fails to conform to what is required or anticipated, the engineer-of-record for the facility can be charged with negligence and may bear liability for damages arising from that failure. An engineer's negligence is assessed by arranging the engineer's actions relative to the standard maintenance cost and budget of the profession. This paper briefly describes the meaning and application of the standard of maintenance costs and budgets, and addresses the meaning of maintenance cost and budgeting with regard to engineering. To examine this issue, this paper presents a case study on the operation maintenance phase of 4 university buildings on the campus of National Taiwan University. Using historical data on maintenance and repair over a 42-year period, a cost prediction model using the life-cycle cost (LCC) was determined using three different methods: (I) simple linear regression (SLR); (2) multiple regression (MR); and finally (3) a back propagation artificial neural network (BPN). The research results showed that the BPN model had keen estimation ability. This paper implemented the BPN model in a case study to analyze the problems of maintenance costs and budgeting for university buildings. The paper helps to set a legitimate standard for arranging repair maintenance costs, and proposes a plan and standard for the repair maintenance strategy of structures.
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收藏
页码:215 / 221
页数:7
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