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Analysis of Economic Indicators Using Statistical Methods
Kočárek, Tomáš ; Tereza, Varyšová (referee) ; Novotná, Veronika (advisor)
The goal of this bachelors work is to evaluate the economic health of the company based on the results of the financial analysis of the company and also predict the development of economic indicators in the future while maintaining the existing trends. The work is divided into two parts, the theoretical and the practical part. In the theoretical part I will describe the financial analysis, its methods and procedures, as well as principles of statistical time series. I will continue with practical part in which I will perform the calculation of indicators, assessment and evaluation of their current financial situation. In conclusion, we will use statistical methods to predict developement in the near future and make suggestions for improvement of the economic situation.
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Implementation and practical verification of methods for predictive identification of rolling bearings failures
Bár, Martin ; Havránek, Zdeněk (referee) ; Klusáček, Stanislav (advisor)
The aim of this thesis is to identify and classify rolling bearing failures. The first part of the thesis deals with the diagnosis of bearings using in-house measured data. Faults were introduced into two bearings. The first one was deformed and corroded. In the second bearing, the outer raceway was damaged. Vibration data was collected at regular intervals and processed in MATLAB. The values of the statistical features indicated faults in both bearings. Envelope analysis showed that both bearings had developed a fault on the outer raceway and a gradual fault on the cage. In the second part of this thesis, machine learning methods were used to classify defective bearings using the CWRU data set. The accelerometer data were divided into blocks in two ways. Vibration images were created from these blocks for convolutional neural networks (CNNs). The best prediction accuracy was achieved by 1D convolutional neural network (1DCNN) (99.2 %), followed by neural network (94.6 %) and SVM (94.4 %). Random Forest and SVM are the best methods when the training set is reduced, and among CNNs, MATLAB architecture and 1DCNN are the best. The most noise resistant method is Random Forest and neural network, and among CNNs, 1DCNN is the best. Methods using statistical features perform better than CNNs on extremely noisy data. Convolutional networks do not achieve good accuracy, which is probably due to the conversion of raw accelerometer data into vibration images.
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Application of Management Control System in a Business
Foralová, Eliška ; Filkuka, Luboš (referee) ; Žižlavský, Ondřej (advisor)
The intention of this diploma thesis is to expound the issue of controlling in a selected company. The diploma thesis is divided into three key sections. The first is the theoretical part, which contains defined concepts such as controlling, reporting or profit centers, on which this work is based in other sections. The analytical part describes the current situation of the selected company for the elaboration of the diploma thesis. In the last part, based on the findings from the previous analytical part, a proposal for improvement is made.
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Creation and application of the system of financial evaluation
VLASENKO, Elizaveta
The bachelor thesis is devoted to the creation of a system of financial evaluation of companies using data from financial reports. Types of statistical indicators and possible ways of their formal systematization are known, but there is no single evaluation system for each individual business. The purpose of this work is to propose an evaluation system for a particular company Mlékárna Kunín, s.r.o on the basis of financial indicators and the choice of existing evaluation methods. The analysis is based on the analysis of problem areas of the company using classical ratio indicators and prediction models. The company's industry and competitive situation are also taken into account. The conclusion of the analytical part is an assessment of both the results for the further development of the company as well as the functionality of the proposed methodology.
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Implementation and practical verification of methods for predictive identification of rolling bearings failures
Bár, Martin ; Havránek, Zdeněk (referee) ; Klusáček, Stanislav (advisor)
The aim of this thesis is to identify and classify rolling bearing failures. The first part of the thesis deals with the diagnosis of bearings using in-house measured data. Faults were introduced into two bearings. The first one was deformed and corroded. In the second bearing, the outer raceway was damaged. Vibration data was collected at regular intervals and processed in MATLAB. The values of the statistical features indicated faults in both bearings. Envelope analysis showed that both bearings had developed a fault on the outer raceway and a gradual fault on the cage. In the second part of this thesis, machine learning methods were used to classify defective bearings using the CWRU data set. The accelerometer data were divided into blocks in two ways. Vibration images were created from these blocks for convolutional neural networks (CNNs). The best prediction accuracy was achieved by 1D convolutional neural network (1DCNN) (99.2 %), followed by neural network (94.6 %) and SVM (94.4 %). Random Forest and SVM are the best methods when the training set is reduced, and among CNNs, MATLAB architecture and 1DCNN are the best. The most noise resistant method is Random Forest and neural network, and among CNNs, 1DCNN is the best. Methods using statistical features perform better than CNNs on extremely noisy data. Convolutional networks do not achieve good accuracy, which is probably due to the conversion of raw accelerometer data into vibration images.
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Application of Management Control System in a Business
Foralová, Eliška ; Filkuka, Luboš (referee) ; Žižlavský, Ondřej (advisor)
The intention of this diploma thesis is to expound the issue of controlling in a selected company. The diploma thesis is divided into three key sections. The first is the theoretical part, which contains defined concepts such as controlling, reporting or profit centers, on which this work is based in other sections. The analytical part describes the current situation of the selected company for the elaboration of the diploma thesis. In the last part, based on the findings from the previous analytical part, a proposal for improvement is made.
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Analysis of Economic Indicators Using Statistical Methods
Kočárek, Tomáš ; Tereza, Varyšová (referee) ; Novotná, Veronika (advisor)
The goal of this bachelors work is to evaluate the economic health of the company based on the results of the financial analysis of the company and also predict the development of economic indicators in the future while maintaining the existing trends. The work is divided into two parts, the theoretical and the practical part. In the theoretical part I will describe the financial analysis, its methods and procedures, as well as principles of statistical time series. I will continue with practical part in which I will perform the calculation of indicators, assessment and evaluation of their current financial situation. In conclusion, we will use statistical methods to predict developement in the near future and make suggestions for improvement of the economic situation.
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Changes of body conformation of Old Kladruby horses
KARDOVÁ, Lenka
Horses have been companions to humans for thousands of years, both as work animals and as part of our culture. The Old Kladruber horse is a Czech autochthonous breed included in animal genetic resources. The aim of my thesis was to assess the gradual change in the external features of Old Kladruber horses in the years 1900 2013 in both the colour variants. I focused on 5 body measurements (height at the withers measured by tape, height at the withers measured by stick, girth of chest, girth of bone) collected for 1021 horses registered in the breed registry. The obtained values have been summarized and subsequently statistically and graphically evaluated. The results imply that values of wither height of Old Kladruber horses measured both by tape and stick have been increasing, whereas their weight has slightly dropped. In white horses, the average increase in the tape-measured wither height amounted to 3.5 cm and to 7 cm in black horses. Stick height at the withers has shown an increase ranging between 3 4.7 cm in white horses, while in black horses, the values ranged between 6 10 cm. In stallions, the chest girth was determined at 197.5 cm. White mares had a chest girth of 199.55 cm. Almost identical value, i.e. 198.13 cm, was determined for black mares. The bone girth has remained almost unchanged. A slight decrease was observed in white Old Kladruber horses stallions in the years 1970 2013 by 0.5 cm. This change was most probably caused by the addition of blood of other breeds in the past. A drop in the weight was monitored over the time interval of 1930 2013 and it ranged between 22 kg and 73 kg according to the monitored group. This drop in the weight and increase in the body frame implies a change in the type of the horse, tending rather to the sports type. However, this change can also be affected by the conditions in the environment. Only in unique cases, the values of the variation coefficient in the years 1990 2013 exceeded the limit of 10%. Groups of monitored horses of both colour variants can thus be considered balanced. In the years 1990 2013, several horses of a non-compliant standard height were also included in the breed. This was required as part of the attempt to preserve all of the existing lines and families as well as to keep the coefficient of relationship low.
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