Site Selection of Precast Concrete Component Factory Based on PCA and GIS

5Citations
Citations of this article
15Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

In China, with the expansion of the prefabricated construction market, the demand for precast concrete (PC) components is increasing and the construction of production plants to meet this need is expanding. To address the problem of siting PC component plants in China's construction industry, a combination of qualitative and quantitative analysis using principal component analysis (PCA) and geographic information system (GIS) is proposed for their siting. Taking the site selection process of a PC component plant in Wuhan, Hubei Province, China as an example, the diamond model is combined with six dimensions of environmental factors, requirements, regional competition, related and supporting industries, technological innovation and policies and regulations to construct an indicator system for PC component plant site selection. In the preliminary selection stage, PCA was applied to analyze the site selection indexes to obtain the overall score and ranking of each district for the selection of PC component plants in Wuhan, and it was concluded that three districts, namely, Xinzhou, Hannan, and Huangpi, were more suitable for the construction of component plants. In the precise selection stage, based on the availability of data, Hannan was selected among the three areas suitable for site selection for GIS analysis, using the visual-spatial analysis function of GIS to quantify the four geographical information indicators of environmental factors, and the results showed that Area C in Hannan was the most suitable area. The results show that the method has high accuracy and good applicability.

Cite

CITATION STYLE

APA

Wang, S., Ruan, Y., & Hu, W. (2022). Site Selection of Precast Concrete Component Factory Based on PCA and GIS. Advances in Civil Engineering, 2022. https://doi.org/10.1155/2022/7857647

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free