Improved Similarity Measure in Case-Based Reasoning with Global Sensitivity Analysis: An Example of Construction Quantity Estimating

被引:23
作者
Du, Jing [1 ]
Bormann, Jeff [2 ]
机构
[1] Univ Texas San Antonio, Dept Construct Sci, San Antonio, TX 78207 USA
[2] Zachry Holdings Inc, Dept Project Controls, San Antonio, TX 78221 USA
关键词
Conceptual cost estimation; Quantity takeoff; Case based reasoning; Global sensitivity analysis; Sobol's TSI; Artificial neural networks; Principal component analysis; AGENT-BASED SIMULATION; NEURAL-NETWORK; MATHEMATICAL-MODELS; REGRESSION-ANALYSIS; GENETIC ALGORITHMS; COST-ESTIMATION; DESIGN; SYSTEM; FRAMEWORK; ISSUES;
D O I
10.1061/(ASCE)CP.1943-5487.0000267
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In recognition of the importance of historical knowledge in decision making, case based reasoning (CBR) is utilized as a form of an expert system to tackle construction management issues such as quantity takeoff in the proposal development phase of a project. It builds on a proposition that past projects similar to the new one would suggest a reasonable range of craft quantities. This paper finds that when measuring the similarity between the new project and historical projects, traditional similarity measure methods fail to consider the nonlinearity and muticollinearity embedded in the problem, as well as differences across crafts. An innovative similarity measurement algorithm was therefore proposed to tackle the above issues with a carefully designed orthogonalization process and Sobol's total sensitivity analysis. The application of the proposed algorithm to the craft quantity takeoff of a power plant project was introduced, demonstrating a better result compared with traditional methods. It is likely that the proposed algorithm will advance current CBR practices in construction management.
引用
收藏
页数:18
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