This work deals with stock market prediction via technical and psychological analysis. We introduce theoretical resources of technical and psychological analysis. We also introduce some methods of artificial intelligence, specially neural networks and genetic algorithms. We design a system for stock market prediction. We implement and test a part of system. In conclusion we discuss results.

The work deals with several theoretical methods of valuation of real estate and the actual valuation of a property using these methods in order to use the evaluation for insurance purposes. It also deals with legal aspects regulating the issue of a valuation. In the practical part of the work, valuations of a nursing home and a house are carried out for comparison. For each case, one of the methods of valuation is used. In the following summary, the outputs are analyzed both for given examples separately and compared together along with data obtained from insurance companies.

In this thesis, an approach to automatically derive information about land cover from the remotely sensed data is presented. The data interpretation was done with classification process and performed in software eCognition Developer. The Object-based image analysis, which assignes the classes - for example land cover types, to clusters of pixels (=objects), was used. For the classification, products of two different data sources were combined - the orthophotos generated from aerial imagery and Normalized Digital surface model derived from LiDAR data. Five types of landscape elements were identified and classified.

The aim of this master’s thesis is comparing prices of building materials wi-thin the building structure in Czech Republic with prices in Poland. The first, theo-retical, part describes differences among the construction classifications and pri-ces. At the end of this theoretical part is written about price calculation of building materials. Specifically about creations of that calculations and comparing between Poland and Czech Republic. The second part is concentrated on created budget and mainly on his bill of materials. The result part is made by comparing of chosen building material pri-ces..

The ROC (Receiver Operating Characteristic) curve is a projection of two different cumulative distribution functions F0 and F1. On axis are values 1-F0(c) and 1-F1(c). The c-parameter is a real number. This curve is useful to check quality of discriminant rule which classify an object to one of two classes. The criterion is a size of an area under the curve. To solve real problems we use point and interval estimation of ROC curves and statistical hypothesis tests about ROC curves.

This diploma thesis deals with posibilities of using structural methods for recognition objects in a picture. The first part of this thesis describes methods for preparing the picture before processing. The core of the whole thesis is in chapter 3, where is analyzed in details the problem of the formation of deformation grammars for parsing and their using. In the next part is space for syntactic parser describing the deformation grammar. The conclusion is focused on testing the suggested methods and their results.

This thesis is oriented to a specific section of energetics concerned with detection and registration of time responses of fast overvoltages in high-voltage power networks. The first part of this text is information about measuring frequency response characteristics of CR-divider and calculation of typical signal distortion caused by transfer function of this divider. The design of anti-aliasing filter is also included. The second part of this thesis is oriented to selecting key features of a measuring instrument specialized for detecting and recording fast events in electrical power networks. A selection of optimal type of processor and also a choice of communication interfaces is included there as well. The last chapter prepares mathematical procedures for classification of typical fast events in electrical power network using artificial neural networks.

This thesis explains business process mining and it's principles. A substantial part is devoted to the problems of process discovery. Further, based on the analysis of specific manufacturing process are proposed three methods that are trying to identify shortcomings in the process. First discovers the manufacturing process and renders it into a graph. The second method uses simulator of production history to obtain products that may caused delays in the process. Acquired data are used to mine frequent itemsets. The third method tries to predict processing time on the selected workplace using asociation rules. Last two mentioned methods employ an algorithm Frequent Pattern Growth. The knowledge obtained from this thesis improve efficiency of the manufacturing process and enables better production planning.

This master's thesis deals with knowledge discovery and is focused on data stream classification. Three ensemble classification methods are described here. These methods are implemented in practical part of this thesis and are included in the classification system. Extensive measurements and experimentation were used for method analysis and comparison. Implemented methods were then integrated into Malware analysis system. At the conclusion are presented obtained results.

This paper deals with the information retrieval in research portals with the intention of the retrieval in scientific publications. We define concepts related to the information retrieval, classification and knowledge representation. We also present existing search tools used as the initial inspiration for the design of the search intergace. Futhermore we describe the implementation as well as the process of collecting sample data. In the last chapter we discuss usability of the developed web application.