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Dynamics of orchid occurrence in highlands
Černocká, Veronika ; Kindlmann, Pavel (advisor) ; Křenová, Zdeňka (referee)
All species of orchids are sensitive plants and records of their distribution are rare. Their rarity is related to their complex biology and their sensitivity to changes in the environment. It is necessary to pay attention to these threatened species, so that we could preserve them from extinction. For their effective protection we need to know the main causes of extinction of their localities. It is also useful to know the factors, which determine their distribution, so that we could find new localities, where they occur. In this thesis I analyzed some climatic, geographic and ecological factors in the Jeseníky mountains and their surroundings. First, I visited localities of orchids, which were registered in large databases of their presence in the past. The four most numerous species were analyzed using the program MaxEnt. Based on the revisions, existence of 2/3 of the revised localities was confirmed, 8% of the revised localities became extinct because of overgrowth or due to human intervention in the landscape. From the MaxEnt results it is clear, that for all species the most important factor at the 50 × 50 m scale, is the type of biotope and heterogeneity of the countryside. The most suitable biotopes are floodplain and wetland forests, mesophile meadows, natural scrubs, peat bogs and...
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Assessing Selected Indicators Using Statistical Methods
Miléřová, Eliška ; Mucalová, Marcela (referee) ; Doubravský, Karel (advisor)
The bachelor thesis deals with an evaluation of the financial situation of the company. The first part presents the theoretical starting points. The practical part contains selected indicators of financial analysis, analysis of time series and regression analysis of the company for the period from 2009 to 2016. With the help of regression analysis, predictions of the future development of selected indicators are provided. Suggestions on improving the current situation of company are processed based on the relults.
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Analysis of Economic Indicators of the Selected Company Using Statistical Methods
Lacko, Matej ; Šustrová, Tereza (referee) ; Novotná, Veronika (advisor)
The diploma thesis deals with the analysis of economic indicators of Technos a.s., using statistical methods and the evaluation of the current financial situation. The work contains a theoretical and practical part. The theoretical part describes selected economic indicators, regression analysis, time series and correlation analysis. In the practical part, the analysis of selected economic indicators will be carried out and then statistical methods will be used to determine the prediction for the next year and to reveal the dependence between the individual indicators. The last part of the thesis deals with proposals that will improve the financial situation of the company.
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Mathematical and Statistical Methods as Support of the Development of Software Applications
Kinc, Petr ; Novotná, Veronika (referee) ; Šustrová, Tereza (advisor)
This diploma thesis focuses on the design and development of the software tool using C# programming language and his subsequent implementation into the Microsoft Dynamics NAV information system. The task of this tool is to analyze the development of selected indicators using statistical methods and to predict their future development. On the basis of these predicted data, is created an indicative budget to support decision making on the determination of key accounting parameters and coefficients for the next accounting period in the company Vodovody a kanalizace Hodonín, a.s.
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Assessing Selected Indicators Using Statistical Methods
Hofmanová, Aneta ; Michalíková, Eva (referee) ; Doubravský, Karel (advisor)
Master's thesis deals with the assessment of selected financial indicators of the company through a financial analysis and statistical methods, on the basis of which then evaluates the current situation of the company. The thesis is divided into three parts. The theoretical part contains the issues necessary for the analytical part. The analytical part is focused on the analysis of selected indicators and the subsequent application of statistical methods to predict their future development and to detect dependencies between the indexes. The last part formulates possible solutions to problems caused by financial indicators that do not reach the required values.
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Assessing of the Financial Situation of a Company Using Time Series Analysis
Kalousková, Petra ; Musilová, Martina (referee) ; Doubravský, Karel (advisor)
The diploma thesis deals with an assessment of the topical financial situation of BARVY A LAKY TELURIA, s. r. o. using the time series analysis. The theoretical part focuses on the description of the financial indicators, analysis of the time series, and subsequently the regressive and correlative analysis. In the practical part, selected financial indicators are statistically analyzed. The future two-year development of indicators is predicted on the basis of the selected models; subsequently dependencies among the particular indicators are determined. In the conclusion, proposals to ameliorate the current financial situation of the company are recommended, which was carried out on the basis of the identified shortcomings.
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Echo state neural network for stock market prediction
Pospíchal, Ondřej ; Mašek, Jan (referee) ; Burget, Radim (advisor)
This thesis deals with an echo state network and with acceleration of its learning by implementing the echo state network on a graphics processor. The theoretical part consists of the description of neural networks and some selected types of neural networks, on which is based the echo state network. After that, there are some other algorithms described used for time series analysis and last but not least, the tools that were used in the practical part of the thesis were briefly described. The practical part describes the creation of the accelerated version of the echo state network. After that, there is described the creation of input data sets of real financial indexes, on which the echo state network and the other algorithmns were then tested. By analyzing this accelerated version it was found that its learning speed did not reach the theoretical expectations. The accelerated version works slower, but with greater precision. By analyzing the results of the measurement of the other algorithmns it was found that the highest precision is achieved by solutions based on the neural network principle.
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Creating predictions average monthly flow for the control of the storage capacity of a fictive reservoir dam
Hrabinová, Barbora ; Sobek, Martin (referee) ; Menšík, Pavel (advisor)
The diploma thesis is focused on predictions of mean monthly flows for a purpose of control of storage functions when thinking differently positions of fictive reservoirs in the catchment area. One of the reservoir is situated in the upper part of the catchment area and the second is situated in the middle part of catchment area. Predictions are made by Support vector machine method in RStudio and with the use of R language. Predicted values of flows was evaluated by the correlation coefficient, coefficient of determination, Root mean square error and than was made the simulation of operation of storage function, which was evaluated by Total sum of squares modificated for problems of water management. In the end was made a comparison of both of the reservoirs for assessment of the suitability of the method.
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Analysis and prognosis of elite male and female triathletes performance at the ITU World Triathlon Championships in 1989-2016 in Olympic Triathlon
Látová, Lenka ; Kovářová, Lenka (advisor) ; Suchý, Jiří (referee)
Title: Analysis and prognosis of elite male and female triathletes performance at the ITU World Triathlon Championships in 1989-2016 in Olympic triathlon Objectives: To analyse male and female performance in individual parts of the triathlon (swim, bike, run) as well as the whole race performance during the years 1989 - 2016. To determine the performance prediction of racers using the time series analysis for Olympic triathlon in ITU World Triathlon Championship in 2028. Methods: For statistical data processing we will apply the time series analysis using SPSS Statistics 22 software. We will then add the historical content and the actual conditions of the race to the final graphs. On the basis of the processed data, we will create a performance prediction for 2028 using Excel program. Results: In swimming, women are approaching men's performance and they are now on 92.2%. In the future, women will not come closer to men's times. Performance will improve slightly. In cycling, the gap between men and women is 10%. We do not expect any major change in the future. According to the trend of development, we find deterioration in both categories, especially in men. At the moment, the performance of women in running is 88.3% of men. We do not expect any change in the future. However, male and female times...
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