Data mining for intelligent structure form selection based on association rules from a high rise case base

Authors:
Shihai Zhang;Shujun Liu;Jinping Ou
Affiliations:
School of Civil Engineering, Harbin Institute of Technology, Harbin, China and Department of Civil Engineering, Nanyang Institute of Technology, Nanyang, China;School of Civil Engineering, Harbin Institute of Technology, Harbin, China;School of Civil Engineering, Harbin Institute of Technology, Harbin, China
Venue:
PAKDD'07 Proceedings of the 2007 international conference on Emerging technologies in knowledge discovery and data mining
Year:
2007

Citing 2
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Abstract

This paper presents a uniform model for high-rise structure design information and a case base containing 1008 high-rise buildings around the world. A case management system has been implemented with functions of data recording, modification, deletion, inquiry, statistical analysis and knowledge discovery. We propose a data-mining process of mining quantitative association rules for structure form selection from the case base and a method for mining fuzzy association rules. In the fuzzy association rule mining, we present a method for fuzzy interval division and fuzzification of quantitative attributes of the real cases. We demonstrate the application of the Apriori algorithm to generate association rules that can be used in building design. This data mining approach provides a new technical support for design efficiency, quality and intelligence.