NDLI: Research on Real Estate Early Warning System Based on Decision Tree and Fuzzy Recognition Theory

Content Provider	IEEE Xplore Digital Library
Author	Jian-zhou Wang Jin-xing Che Jin-zhao Liang Haiyan Lu
Copyright Year	2008
Description	Author affiliation: Sch. of Math. & Stat., Lanzhou Univ., Lanzhou (Jian-zhou Wang)
Abstract	This paper presents a pre-warning system developed to monitor and provide pre-warning to the governmental decision makers in real estate market, applying the grey relational analysis and model design method, with the fuzzy recognition theory based on decision tree and its effectiveness. The real estate early warning system has been designed successfully by the three sub-modules of feature selection on each non-terminating node, decision rule on each non-terminating node and a new fuzzy decision tree method, early warning for the real estate market. The article details analysis and recognition module, a set of factors are selected by grey relational analysis and fuzzy recognition early-warning method is used, which can monitor the real estate property market, is developed. Empirical results indicate that the pre-warning system can provide useful information to regulate the property market.
Starting Page	414
Ending Page	418
File Size	316754
Page Count	5
File Format	PDF
ISBN	9780769533056
DOI	10.1109/FSKD.2008.24
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Real estate market Statistical analysis Design methodology early warning Mathematics fuzzy membership function decision tree Investments Alarm systems Economic forecasting Decision trees fuzzy recognition Monitoring Fuzzy systems Classification tree analysis
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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