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Methods of Residental Real Estate Valuation in Austria
Partlová, Lucie ; Hlavinková, Vítězslava (referee) ; Klika, Pavel (advisor)
This thesis deals with residential real estate market in the Austria and its development. The theoretical part defines the basic concepts of valuation, such as flat, family house, usual price, valuation legislation, expert opinion and summary methods of residential property valuation in Austria. The other part is targeted of the property market. The practical part deals with valuation of real estates in selected ways. In thesis attachment is processed an exemplar of the evalution report for a flat according to the standards and the methodologies used to by the evaluation in the Austria.
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Methods of Residental Real Estate Valuation in Austria
Partlová, Lucie ; Hlavinková, Vítězslava (referee) ; Klika, Pavel (advisor)
This thesis deals with residential real estate market in the Austria and its development. The theoretical part defines the basic concepts of valuation, such as flat, family house, usual price, valuation legislation, expert opinion and summary methods of residential property valuation in Austria. The other part is targeted of the property market. The practical part deals with valuation of real estates in selected ways. In thesis attachment is processed an exemplar of the evalution report for a flat according to the standards and the methodologies used to by the evaluation in the Austria.
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Application of the Artificial Intelligence in the Real Estate Valuation
Štechová, Edita ; Witzany, Jiří (advisor) ; Fičura, Milan (referee)
The main purpose of this study is to develop a predictive model capable to forecast residential real estate prices in the city of Prague using Artificial Intelligence methods. The first part of this study discusses fundamentals of Artificial Neural Networks and Fuzzy Inference Systems in the context of real estate valuation. The second part demonstrates a development and testing of such models using a dataset of real estate market transactions. In the third part, results are compared to Multiple Regression and an explanatory power of each model is evaluated. Conclusions of this research are: (1) Artificial Neural Networks and Fuzzy Inference Systems give more accurate estimates of market values of residential real estates than Multiple Regression; (2) Artificial Neural Networks and Fuzzy Inference Systems represent an efficient way of modeling and analyzing residential real estate prices in Prague.
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