|
|
The notation analyses of goals during ice-hockey word championship 2021 in U20 category
Janoušek, Jakub ; Šťastný, Petr (advisor) ; Vojta, Zdeněk (referee)
Objectives: The ai m of this diploma thesis is to analy s e goals scored in WJC 2021 and comparison countrie s . The second aim is to detect the biggest demerits of czech hockey from scoring view point w ith the help of this facts and inspire other coaches to more intensive work a greed with wold trend in this topic and the aim to return czech hockey to the best hockey countries group. Methods: The research was carried out by indirect observations 28 matches and 176 scoring situations through video records from WJC 21. The subject of research were 10 teams, that selected 88 scorers. Scoring situations were qualitative analyse. Gained findings have been written down into chart and were quantitative analyse. Results: The outcome of analyse is the most used scoring place Low slot - 0 - 10ft in front of the goal and with the most used location of successfull shot - middle of the goal on the ice or close over the ice creates the most used way to score. From w rist shot - forehand side came the most of goals in WJC 21. Analyse proved demerits o f Czech national team U20 in scoring by tip - in and rebound. The result of analyse also proved demerits of Czech select in power play and short - handed play. Keywords: Ice hockey, WJC 21, shooting, scoring, scoring range, shooting metodology
|
|
|
Hodnocení bonity klientů při získávání úvěru v bance
Šlapalová, Anežka
The diploma thesis is focused on the appreciation of clients' creditworthiness in obtaining loans at Komerční banka, a.s., which is one of the largest and most widely used banks in the Czech Republic. The work is divided into literary research and practical part. Literary research characterizes and explains the basic concepts of credit management and credit analysis. There are described different methods and models for assessing the creditworthiness of clients, which are further used in the practical part and are the basis for assessing the client's creditworthiness. The second part of the thesis analyzes Komerční banka, a.s., where its loan products are analyzed, and specific credit processes and credit analyzes are explained in model cases.
|
|
|
Choice of swimming method, the most common mistakes when swimming with applicants for study at the Faculty of Education of Charles University
Papežová, Šárka ; Svobodová, Irena (advisor) ; Pokorný, Ladislav (referee)
TITLE The Choice of the swimming method, the most common mistakes when swimming with applicants for study at the Faculty of Education of Charles University AUTHOR Šárka Papežová DEPARTMENT Department of physical education SUPERVISOR PaedDr. Irena Svobodová ABSTRACT This thesis deals with the choice of swimming strokes in entrance examinations for a study at the College of Education, Charles University, and it also analyses the most common mistakes in individual swimming strokes with reference to accepted swimming rules. The problem is approached from the perspective of academic field of Physical Education and Teaching for Kindergartens and it is analysed with view of sex and age of the candidates. The thesis also turns to the characteristics of individual swimming strokes and mistakes in swimming. Statistical analysis of 5 years of records of entrance examinations were used in preparation of this thesis. KEYWORDS Swimming method, the front crawl, the breaststroke, the backstroke, respiration during swimming, statistic, physical education, teaching for infant school
|
|
| |
|
|
Artificial Intelligence Approach to Credit Risk
Říha, Jan ; Baruník, Jozef (advisor) ; Vošvrda, Miloslav (referee)
This thesis focuses on application of artificial intelligence techniques in credit risk management. Moreover, these modern tools are compared with the current industry standard - Logistic Regression. We introduce the theory underlying Neural Networks, Support Vector Machines, Random Forests and Logistic Regression. In addition, we present methodology for statistical and business evaluation and comparison of the aforementioned models. We find that models based on Neural Networks approach (specifically Multi-Layer Perceptron and Radial Basis Function Network) are outperforming the Logistic Regression in the standard statistical metrics and in the business metrics as well. The performance of the Random Forest and Support Vector Machines is not satisfactory and these models do not prove to be superior to Logistic Regression in our application.
|
|
| |
|
|
Improved Prediction of Social Tags Using Data Mining
Harár, Pavol ; Galáž, Zoltán (referee) ; Kříž, Jiří (advisor)
This master’s thesis deals with using Text mining as a method to predict tags of articles. It describes the iterative way of handling big data files, parsing the data, cleaning the data and scoring of terms in article using TF-IDF. It describes in detail the flow of program written in programming language Python 3.4.3. The result of processing more than 1 million articles from Wikipedia database is a dictionary of English terms. By using this dictionary one is capable of determining the most important terms from article in corpus of articles. Relevancy of consequent tags proves the method used in this case.
|
|
|
Default Risk Modeling in Chemistry Industry
Jedlička, Jaromír ; Czekus, Robert (referee) ; Režňáková, Mária (advisor)
My thesis is focused on the presentation of a scoring model for companies in chemical industry with use of cluster analysis methods. There is a description of financial risks, financial analysis indicators and models which are used to evaluate financial risks of a company. There is also a mathematical description of hierarchical cluster methods.
|
|
|
Credit risk management in banks
Pětníková, Tereza ; Blahová, Naděžda (advisor) ; Šedivý, Jan (referee)
The subject of this diploma thesis is managing credit risk in banks, as the most significant risk faced by banks. The aim of this work is to define the basic techniques, tools and methods that are used by banks to manage credit risk. The first part of this work focuses on defining these procedures and describes the entire process of credit risk management, from the definition of credit risk, describing credit strategy and policy, organizational structure, defining the most used credit risk mitigation tools to the regulatory requirements for credit risk management. The second part gives a more detailed view to credit risk measurement and evaluation and possibilities of credit risk hedging. Last part presents credit risk management in practise illustrated by the example of chosen bank.
|
|
|
The Estimation of Probability of Default Using Logistic Regression
Chalupa, Tomáš ; Dlouhá, Zuzana (advisor) ; Formánek, Tomáš (referee)
The aim of this work is to develop a suitable model that estimates a probability of default of client's loan. As estimation method was used a logistic regression and a probit regression and two definitions of default, 60 and 90 days overdue. The work describes the method of construction, estimation and testing of scoring models and a structure of dataset, which was used in the practical part. Firstly, it was created a theoretical model that was later confronted with estimates. Estimated models were compared by described statistics as McFadden R^2, the ability to diversify was investigated by the Lorenz curve and by the Gini coefficient. It was found that the logistic and the probit regressions have almost the same results, and that 90 days is preferable definition of default than 60 days.
|
guest ::
