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Decision making based on partially known decision trees
Poláček, Tomáš ; Dostál, Petr (referee) ; Koutský, Jaroslav (referee) ; Váchal, Jan (referee) ; Dohnal, Mirko (advisor)
There is a wide range of different algorithms for insolvency prediction. The complex concept of insolvency proceedings from the point of view of both parties (debtor versus creditor) and from the point of view of the macroeconomics in this dissertation is new. It is often very difficult to generate forecasts using numerical quantifiers and traditional statistical methods. The reason is the lack of input data. Therefore, the work uses trend analysis tools based on the least information intensive quantifiers, ie trends, increasing, constant, and decreasing. A trend model solution is a set of scenarios where a set of variables is quantified by these trends. All possible transitions between the scenarios are generated and plotted in transition graphs. The oriented transition graph has as a node a set of scenarios, and as a branch the transitions between the scenarios. The given path through the transition graph describes any possible future and past behavior of the insolvency system being investigated. The Transition graph is a complete list of trend-based forecasts. The heuristics for determination of the payoff values from the insolvency proceedings applicable to the decision tree tools and the generated transition graphs from trend analyzes are also presented and used in the thesis. A nine-dimensional model serves as a case study. Vague variables are used in models that may have a major impact on the entire insolvency process, eg greed level and political situation.
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Decision making based on partially known decision trees
Poláček, Tomáš ; Dostál, Petr (referee) ; Koutský, Jaroslav (referee) ; Váchal, Jan (referee) ; Dohnal, Mirko (advisor)
There is a wide range of different algorithms for insolvency prediction. The complex concept of insolvency proceedings from the point of view of both parties (debtor versus creditor) and from the point of view of the macroeconomics in this dissertation is new. It is often very difficult to generate forecasts using numerical quantifiers and traditional statistical methods. The reason is the lack of input data. Therefore, the work uses trend analysis tools based on the least information intensive quantifiers, ie trends, increasing, constant, and decreasing. A trend model solution is a set of scenarios where a set of variables is quantified by these trends. All possible transitions between the scenarios are generated and plotted in transition graphs. The oriented transition graph has as a node a set of scenarios, and as a branch the transitions between the scenarios. The given path through the transition graph describes any possible future and past behavior of the insolvency system being investigated. The Transition graph is a complete list of trend-based forecasts. The heuristics for determination of the payoff values from the insolvency proceedings applicable to the decision tree tools and the generated transition graphs from trend analyzes are also presented and used in the thesis. A nine-dimensional model serves as a case study. Vague variables are used in models that may have a major impact on the entire insolvency process, eg greed level and political situation.
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