DocumentCode :
483216
Title :
Study on the Risk Prediction of Real Estate Investment Whole Process Based on Support Vector Machine
Author :
Li, Wanqing ; Zhao, Yong ; Meng, Wenqing ; XU, Shipeng
Author_Institution :
Sch. of Econ. & Manage., HeBei Univ. of Eng., Handan
fYear :
2009
fDate :
23-25 Jan. 2009
Firstpage :
167
Lastpage :
170
Abstract :
With the rapid development of real estate, the risk of investment is also increasing rapidly. So the risk of predicting and controlling the real estate investment has become the key to the success or failure of the project. In this paper, a support vector machine (SVM) modeling approach for real estate investment risk prediction is proposed at first, which is made use of its merits of structural risk minimization principle, the small study sample and non-linear to analyze the risk factors during investment every stage in real estate projects, then a model based on support vector machines in real estate investment risk is built up, at last, an example is given to prove that this model is effective and practical. All these are used of providing useful help of the future of real estate investment risk control and management.
Keywords :
investment; minimisation; real estate data processing; risk analysis; support vector machines; real estate investment; risk prediction; structural risk minimization principle; support vector machine; Data engineering; Economic forecasting; Engineering management; Investments; Knowledge engineering; Knowledge management; Predictive models; Risk analysis; Risk management; Support vector machines; Fully Mechanized Mining Face; Prediction; Support Vector Machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Knowledge Discovery and Data Mining, 2009. WKDD 2009. Second International Workshop on
Conference_Location :
Moscow
Print_ISBN :
978-0-7695-3543-2
Type :
conf
DOI :
10.1109/WKDD.2009.40
Filename :
4771904
Link To Document :
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