Data Mining of ACO-Based Rough Sets and Application in Construction Projects Cost Analysis

Author

Huawang, Shi ; Huishu, Cao

Author_Institution

Sch. of Civil Eng., Hebei Univ. of Eng., Handan, China

fYear

2009

fDate

25-26 April 2009

Firstpage

251

Lastpage

254

Abstract

In this paper, the reduction algorithm based on rough sets (RS) is proposed as a practical data mining technology. It has been proven that the information system reduction is a NP-hard problem. NP-hard problem is a major property portfolio explosions. Thus, the only solution to this problem is the development of heuristic search method. Ant colony optimization, which was introduced in the early 1990s as a novel technique for solving hard combinatorial optimization problems, finds itself currently at this point of its life cycle.With this article we implying the use of ant colony optimization (ACO) algorithm for resolving the NP-hard problem in rough set attribute reduction. Using ACO-based rough sets, construction projects cost was analyzed and the results show that this method is more convenient and practical compared with the traditional one.

Keywords

construction industry; cost reduction; data mining; optimisation; rough set theory; search problems; ACO; NP-hard problem; ant colony optimization; combinatorial optimization problems; construction project cost analysis; data mining; heuristic search method; information system reduction; property portfolio explosion; rough set attribute reduction; Algorithm design and analysis; Ant colony optimization; Buildings; Costs; Data mining; Floors; Information systems; NP-hard problem; Rough sets; Sections; construction project; cost analysis; data mining; rough sets;

fLanguage

English

Publisher

ieee

Conference_Titel

Database Technology and Applications, 2009 First International Workshop on

Conference_Location

Wuhan, Hubei

Print_ISBN

978-0-7695-3604-0

Type

conf

DOI

10.1109/DBTA.2009.54

Filename

5207769