Kaunas – svarbus transporto, mokslo ir kultūros bei Kauno apskrities, miesto savivaldybės, Kauno rajono savivaldybės centras, antrasis pagal dydį Lietuvos miestas, kuriame aktyviai vykdomi nekilnojamojo turto sandoriai ir šio turto vertinimas.. Tyrimo tikslas – išanalizuoti ir palyginti skirtingais metodais nustatytas nekilnojamojo turto vertes. Tyrimo objektas – vieno, dviejų, trijų, keturių kambarių butai ir namai esantys Kauno mieste. Atliekant šį butų ir namų vertinimo metodų palyginimą, buvo surinkti duomenys apie 2013 metų ir 2014 metų pirmojo ketvirčio nekilnojamojo turto vertes, vertinant skirtingais metodais. Baigiamajame darbe aptariama nekilnojamojo turto vertinimas bei jo metodai bei funkcijos. Pateikiama bendroji Kauno miesto apžvalga. Supažindinama smulkiau su nekilnojamojo turto vertinimo metodais naudotais darbe. Pateikti atlikto tyrimo rezultatai, parodo nekilnojamojo turto vertinimo metodų skirtumus. Taip pat skirtingų nekilnojamojo turto vertinimo metodų pliusus ir minusus. Bei Nekilnojamojo turto vertės priklausomybę nuo tam tikrų veiksnių, vertinant skirtingais vertinimo metodais. / Kaunas is an important center of transport, science and culture, Kaunas city is the center of municipality and district municipality, as well as the central part of the country and the second largest city in Lithuania. The aim of the research - to analyze and compare fixed property values by different methods. The object of the research – houses and apartments consisting of one, two, three, four bedrooms in the Kaunas city. In the comparison of the assessment methods, the data of real estate value of the year 2013 and the first quarter of 2014, based on evaluation by different methods, was collected. This thesis deals with real estate valuation, its methods and functions. A general overview of Kaunas is provided. The methods of real estate valuation applied in research are explained in detail. Research results show the differences between real estate valuation methods. Also, the pros and cons of each method of valuation of real estate are presented. The dependence of the value of real estate on some factors when using different methods is revealed as well.

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.