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Deviations prediction in timetables based on AVL data
Jiráček, Zbyněk ; Martínek, Vladislav (advisor)
Relevant path planning using public transport is limited by reliability of the transportation network. In some cases it turns out that we can plan paths with respect to expected delays and hereby improve the reliability of the resulting path. This study focuses on prediction of the delays in public transport systems using data from vehicle tracking systems -- known as the AVL data. These data are typically collected by the transit operators. Various algorithms are compared using real data from Prague trams tracking system. The study also includes a discussion about a possible utilization of the information gained from the used methods in passenger information systems. Powered by TCPDF (www.tcpdf.org)
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Software using random forest for risk prediction of heart valve surgery patients
HERMANUTZ, Georg
CASPeR - Cardiac surgery prediction tool for risk stratification of heart valve surgeries is presented. The base builds a machine learning pipeline for training a random forest classifier which predicts the mortality after a certain amount of days after the surgery was performed. The classifier also offers a list of potential risk factors through its in build feature selection. With a survival analysis the groups "high-risk" and "low-risk" are compared with each other to check for statistical difference. The tool uses "Shiny" a R package which offers a web frame work to develop data analysis visualizations for the User Interface. CASpeR is delivered as a Microsoft Windows standalone desktop application, that comes with a .exe installer and a detailed manual.
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Bryophytes distribution modelling
Procházková, Martina ; Man, Matěj (advisor) ; Fialová, Lucie (referee)
The aim of this bachelor thesis is to summarize recent knowledge about Species Distribution Modelling in botany, focusing on bryophytes. Species Distribution Modelling is used to explain the relationship between species occurrences and environmental conditions of their habitats. This method has unused potential in bryophytes compared to vascular plants. The distribution of bryophytes is influenced by their dispersal and ecological characteristics. The most important factor is a close association between bryophytes and microclimatic conditions of their habitats. This association is studied, but is not yet incorporated in the modelling process along with using data in an appropriate scale. Currently there is an increased interest in bryophytes distribution modelling. In Europe, there are some studies using this method for bryophytes mainly in Iberian Peninsula, Italy and northern Europe. There are approximately 25 articles focused on bryophytes distribution modelling worldwide. This method can be used for ecological niche modelling, in biogeography and for prediction of distribution in future climate. The use of bryophytes distribution modelling for their conservation is also significant. Bryophytes distribution models can successfully predict potential distribution of rare or endangered species and...
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Data Mining with Python
Šenovský, Jakub ; Bartík, Vladimír (referee) ; Zendulka, Jaroslav (advisor)
The main goal of this thesis was to get acquainted with the phases of data mining, with the support of the programming languages Python and R in the field of data mining and demonstration of their use in two case studies. The comparison of these languages in the field of data mining is also included. The data preprocessing phase and the mining algorithms for classification, prediction and clustering are described here. There are illustrated the most significant libraries for Python and R. In the first case study, work with time series was demonstrated using the ARIMA model and Neural Networks with precision verification using a Mean Square Error. In the second case study, the results of football matches are classificated using the K - Nearest Neighbors, Bayes Classifier, Random Forest and Logical Regression. The precision of the classification is displayed using Accuracy Score and Confusion Matrix. The work is concluded with the evaluation of the achived results and suggestions for the future improvement of the individual models.
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Data Mining for Suggesting Further Actions
Veselovský, Martin ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
Knowledge discovery from databases is a complex issue involving integration, data preparation, data mining using machine learning methods and visualization of results. The thesis deals with the whole process of knowledge discovery, especially with the issue of data warehousing, where it offers the design and implementation of a specific data warehouse for the company ROI Hunter, a.s. In the field of data mining, the work focuses on the classification and forecasting of the advertising data available from the prepared data warehouse and, in particular, on the decision tree classification. When predicting the development of new ads, emphasis is put on the rationale for the prediction as well as the proposal to adjust the ad settings so that the prediction ends positively and, with a certain likelihood, the ads actually get better results.
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Algorithmic Trading Using Artificial Neural Networks
Šeda, Jan ; Černocký, Jan (referee) ; Szőke, Igor (advisor)
The capability to be able to determine the future progression on the worlds stock exchange is an important issue, which has become discernible in the last decades. An important role of this progression lies within the fast advancements in computerized technology. Aforementioned document describes a mechanism used for prediction of the future price of a certain stock. The strategy of trading is build upon this mechanism, and the core of this prediction system is an artificial neural network. Inputs used in this network are indicators derived from technical analysis. This trading system was implemented into historical trades and successfully tested.
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Udržitelnost německého ekonomického modelu v globálních politických změnách: migrace jako výzva nebo příležitost
Lacová, Lucia ; Neumann, Pavel (advisor) ; Novotná, Markéta (referee)
This thesis is devoted to the description of the German economy throughout recent decades including the unification and introduction of the euro. The thesis enumerates the basic features of the German economic model and identifies the main policy failures, as well as successes of its government. An important part of this thesis concerns the consequences of the introduction of euro and the subsequent increase in the competitiveness of the German economy at the expense of the other Eurozone members. The main part of this thesis investigates the economic sustainability of the German economic model in the context of the current European refugee crisis. This thesis focuses mainly on the challenges and opportunities brought by the changing global environment and it examines the changing population trends in Germany and the possible scenarios immigrants can cause. It finds opportunities of how the German economic model could be changed towards the better sustainability.
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The Position of South Korea in Inbound Tourism of Asia and Pacific Region
Dušková, Veronika ; Valentová, Jana (advisor) ; Machová, Božena (referee)
This diploma thesis analyses the position of South Korea in inbound tourism of macro-region Asia and Pacific. The main purpose is to evaluate the current and future potential of South Korea's inbound tourism and to define the position of South Korea in inbound tourism of the region based on detailed statistical analysis and competitiveness evaluation of South Korea. Firstly, South Korea was analysed from the political and economical perspective and later on the thesis focused on preconditions of tourism and tourist regions folowed by statistical analysis of the inbound tourism indicators. Moreover, the tourist arrivals of Czech citizens to South Korea were analysed. The competitiveness of South Korea was evaluated based on GCI and TTCI indexes. Lastly, the future development of international arrivals to South Korea was predicted based on regression analysis.
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