The Effective Classification Process Analysis of the Big Data in Construction Project

Qian An

doi:10.4028/www.scientific.net/AMM.644-650.1749

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 644-650The Effective Classification Process Analysis of...

The Effective Classification Process Analysis of the Big Data in Construction Project

Abstract:

In large construction projects, a single construction features data cannot be found to use as constraint. Traditional data classification methods use multi-feature constraints. Using multiple features for construction data uniqueness expressed has excessive features to express so that affect the efficiency of the classification. This paper proposes a construction project based on discrete transform big data classification. By enhancing the features of the construction project data, use the enhanced identification as the basis data classification, so that the scope of construction data classification can be obtained. Experimental results show that use the improved algorithm to perform big data classification on massive construction projects, it can effectively improve the accuracy of classification.

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Periodical:

Applied Mechanics and Materials (Volumes 644-650)

Pages:

1749-1751

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.644-650.1749

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Online since:

September 2014

Authors:

Qian An*

Keywords:

Construction Project, Data Classification, Discrete Transform

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* - Corresponding Author

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