: Ying Xie, Li Yang, Xiaohang Zhang
Public housing construction has contributed a lot to the economic development in China. Based on the fact that the demand of public housing must be reasonably forecasted, which is an important basis to ensure the sustainable development of the economy, in order to optimize public investment and land resources, there are many uncertain factors to change the medium and long-term middle-lower income families. Considering public housing construction scale typically energy-intensive and resource-intensive activities, especially for the purpose of improving performance of public housing construction in China, in this paper, based on the national statistic data, characteristics of public housing demand have been analyzed. Because of the dynamic nature of public housing demand and the specificity of sample data, leading to forecasting of public housing demand very difficult, so a intelligent estimation model based on least squares support vector machines is presented to improve the forecasting process. The proposed model takes advantage of LS-SVMs ability to solve the problem with small samples and nonlinear regression. Furthermore, the proposed approach is shown more accurate for prediction in the case of real-word application.
:Public housing , Demand, Forecasting
Ying Xie, Li Yang, Xiaohang Zhang, Model of forecasting public housing demand in the capital cities in China based on LS-SVMs,Advances in Industrial Engineering and Management, Vol.2, No.1, pp. 1-4, 2013
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 Pan Yuhong, Shao Huilin, 2009. ‘An Outline of the
Chongqing Construction Industry for Housing
Industrialization’. International Conference on
Management and Service Science , pp. 1-4.
 Hao Deng, Jin Xu & Hong Zeng. 2008, ‘Study on
Measures and Strategies of Use Safety Management
of Buildings in Longgang District of Shenzhen’.
International Conference on Information
Management, Innovation Management and
Industrial Engineering, pp. 490-493.
 Shi, J.J., Zeng, S.X. & Tam, C.M. 1998. ‘Modeling
and simulation of public housing construction in
Hong Kong’, Simulation Conference Proceedings,
 Ibrahim Dincer& Marc A. Rosen. 1999, ‘Energy,
environment and sustainable Development’,
Applied Energy vol 64, pp. 427-440.
 Jun Li,Michel Colombier 2009. ‘Managing carbon
emissions in China through building energy
efficiency,’ Journal of Environmental Management
vol 90, pp. 2436–2447.
 Cherry, S. 2007, ‘How to Build A Green City,’
Spectrum, IEEE , pp.26 - 29.
 Qian Shi & Shoufeng Chen. 2008, ‘Evaluation of
Green Construction Alternatives Based on Value
Engineering,’ WiCOM’08. 4th International
Conference on Wireless Communications,
Networking and Mobile Computing, pp.1–6.
 Shang Chunjing, & Zhang Zhihui. ‘Building a New
Concept System for Construction Quality
Assessment of Life-cycle Carbon Emission for
Buildings,’ Journal of Engineering Management,
2010, pp. 2–6.
 Suykens J A K, & Vandewalle J. 1999, ‘Least Squares
Support Vector Machine Classifiers,’ Neural
Processing Letter, vol. 9(3), pp: 293-300.
 Li Xie, Hua Zheng, Lizi Zhang, Dec. 2007,
‘Electricity price forecasting by
clustering-LSSVM,’ Power Engineering
Conference,IPEC 2007. International, , pp.