DocumentCode
1926721
Title
A system for per capita Floor Space of Residential Buildings forecasting in urban area of China: A case study of Chongqing Municipality
Author
Liu, Guiwen ; Wang, Man ; Deng, Fei
Author_Institution
Fac. of Constr. Manage. & Real Estate, Chongqing Univ., Chongqing, China
fYear
2010
fDate
8-10 Aug. 2010
Firstpage
122
Lastpage
125
Abstract
With the development of economy in China, the living standards of public are becoming increasingly important for the competitiveness of the whole country, while Per Capita Floor Space of Residential Buildings (RB) is an indispensible indicator to measure the living standards of public, especially for the people in urban areas of China. Based on the RB data of Chongqing from 2001 to 2007, this paper analyzes the key influencing factors (KIFs) by applying grey relation analysis (GRA) theory, and introduces systematic gray forecasting theory which is based on Price Indices for Real Estate (PIRE) and Floor Space of Building Completed (FSBC) to forecast the RB of Chongqing Municipality from 2008 to 2015. The results of this research have been applied to the 12th Five-year-plan in Real Estate Industry of Chongqing Municipality. Moreover, this system for RB forecasting can been widely used in urban areas of China, while this is general method to forecast Per Capita Floor Space of Residential Buildings.
Keywords
construction industry; economic cycles; forecasting theory; grey systems; property market; public administration; town and country planning; China; Chongqing municipality; economic development; five-year-plan; gray forecasting theory; grey relation analysis; key influencing factors; per capita floor space; price indices for real estate; public living standards; real estate industry; residential buildings forecasting; urban area; Artificial neural networks; Forcasting; GM(l,N); Key Influencing Factors; Per Capita Floor Space of Residential Buildings; Urban Management;
fLanguage
English
Publisher
ieee
Conference_Titel
Emergency Management and Management Sciences (ICEMMS), 2010 IEEE International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-6064-9
Type
conf
DOI
10.1109/ICEMMS.2010.5563487
Filename
5563487
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