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Commodity Residential Investment Risk Evaluation Basing On Rough Set And Support Vector Machine

Posted on:2016-11-13Degree:MasterType:Thesis
Country:ChinaCandidate:G YueFull Text:PDF
GTID:2309330464956925Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
Evaluation of commodity residential investment risk is the basis of risk management and prevention. However, the commonly used method of risk management has a series of defects, such as strong subjectivity, heavy workload of sample collection, low accuracy of risk prediction, etc. A kind of new method must be introduced.Domestically, it combines Rough Set with Support Vector Machine for the application to investment risk evaluation of commodity residential. The combination of them can mutual reinforce, which is a better solution to the above defects.The main contents of this thesis are as follows:(1) Reviews the domestic and overseas research process about investment risk management of commodity residential, RS, and SVM;(2) Introduces and compares the advantages and disadvantages of commonly used methods to evaluate investment risk;(3) Divides commodity residential investment risk into 24 factors of investment risk of commercial housing;(4) Details basic theory of RS and SVM, and then summarizes their respective advantages and their complementarities while being together applying;(5) Raises the modeling approach of investment risk evaluation of commercial housing based on RS-SVM;(6) In case analyzing, adopts expert evaluation method to collect the quantization value of investment risk factors of several commodity residential districts in Shenzhen,and according to the methods in 5th, obtains every factors weight as well as a predictive model of commodity residential investment risk that have been verified by 10-fold cross-validation.
Keywords/Search Tags:commodity residential, factors of investment risk, Rough Set, Support Vector Machine, 10-fold cross-validation
PDF Full Text Request
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