Dissertation
Dissertation > Economic > Economic planning and management > Economic calculation, economic and mathematical methods > Economic and mathematical methods

Research on System Grey-catastrophe Prediction, Early Warning Model and Theirs Application in Economics

Author GuoYuQiang
Tutor FangZhiGeng
School Nanjing University of Aeronautics and Astronautics
Course Systems Engineering
Keywords system catastrophe economic prediction economic early warning cotastrophe theory
CLC F224
Type Master's thesis
Year 2013
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Catastrophe is a phenomenon that uncontinuous and unsmooth.It occurs in the economic systemfrequently. Catastrophe is a great disturbance for the stable economic system and its effectiveprediction and early-warning is significant.After the catstrophe impact,the environment of theeconomic system is complex and changeable.Predicting the trend of the system is meaningful.In thisstudy,the catastrophe prediction model and early-waring model of the ecomic system is establishedbased on the catastrophe theory,multivariate statistical analysis theory,grey number theory,Bayesianinference theory and grey prediction theory.The main innovative points are as follows.(1)The first model established in this study is Economic Early Warning Model Based onCatastrophe Theory. In this part, principal component analysis, multiple regression analysis andcatastrophe theory is used to establish an early warning model of economy.The model anderected abridge between the social science problem and catastrophe theory. The model has inherited thegraphicaldisplay technology of catastrophe theory,It displays the complex–dynamic-early-warningprocess intuitively.(2)The second model established in this study is Grey Function Analysis Model (1,1). Most ofprediction models use historical data will fail because the catastrophe occurs. This part establishedGFAM(1,1) which is Grey Function Analysis Model(1,1) based on functional theory, BayesianNetwork theory and Interval Grey Number theory. More precise prediction can be made with thismodel which can fully mines the exist data. Least Squares parameters theorem and Prediction theoremare proved and the steps of GFAM(1,1) is given in the article.(3)The third model established in this study is Early Warning Model of the Real Estate in China.The real estate market is essential for the government as well as the populace in China.This partestablished a early warning model for the real estate in China based on the principal componentanalysis,multiple linear regression method and the catastrophe theory.The model displays the trend ofthe real estate market visually,dynamically and systematically and early warns whether the real estatemarket in China occurs an catastrophe.

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