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The Application of Fuzzy Logic for Evaluation of Quality of Customers
Pipková, Zuzana ; Šebestová, Monika (referee) ; Dostál, Petr (advisor)
Presented diploma thesis is involved in the issue of customer evaluation of GALATEK a.s. The main company’s manufacturing program is production of machines for surface treatment. Fuzzy logic models will be used to evaluate customers. This models will be crated in software such as MS Excel and MathWorks MATLAB. First part of the diploma thesis contains theoretical summarization needed to understand whole issue. Basic information about company are presented in second part of the diploma thesis. Third part contains customer evaluation based on co-operation with company, outcomes and proposals which are results of customers evaluation.
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The Use of Artificial Intelligence for Decision Making in the Firm
Března, Filip Samuel ; Šebestová, Monika (referee) ; Dostál, Petr (advisor)
Artificial intelligence and fuzzy logic related to it currently belong to very popular and rapidly expanding technological subjects. It finds use in many areas, which also include the process of prediction of future states based on specific finite input characteristics. This master’s thesis deals with predictions that are done in field of agricultural crops growing. Basic principles that are affecting mentioned agricultural growing are explained here, their meaning and significance are specified, these are later on perceived as a key aspect to creation of fuzzy models that are used for prediction. This process is specifically about finding out the most suitable crop on considered parcel for maximization of income. Second part of design section is dedicated to description of approaches for work with fuzzy models and is also used as demonstration of application created for purpose of this thesis.
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Statistical Analysis of Risk Factors of a Company
Semchiv, Evgheni ; Šebestová, Monika (referee) ; Karpíšek, Zdeněk (advisor)
This master`s thesis deals with the use of statistical and economic methods of analysis for evaluation of the financial situation of Heineken Czech Republic a.s. Company's economic indicators are subjected to regression analysis, interval regression analysis, and time series analysis. The proposal part contains a detailed evaluation of the results of the analyzes, evaluation of the financial risk factors and recommendations for improving the financial situation of the company.
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Project Proposal for the Selected Company’s Reallocation
Procházková, Andrea ; Šebestová, Monika (referee) ; Doskočil, Radek (advisor)
The diploma thesis deals with the management issues, specifically the proposal of the company Ferrokont, s.r.o. and their productive and warehouse areas with using methods and technique of project management. The theoretical part describes elementary knowledge, techniques and methods of project management applying in practical part of the thesis. In introductory part of thesis is performed analysis of current condition of the company with the help of the study opportunities and than created draft of project containing time, resource, cost analysis and followed with risk analysis of the project. Benefits of the project are described in the end of the diploma thesis. Part of the diploma thesis is to create project of Microsoft Project.
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The use of convolutional neural networks for predicting the financial failure of a company
Šebestová, Monika ; Chramcov, Bronislav (referee) ; Lenort, Radim (referee) ; Režňáková, Mária (referee) ; Dostál, Petr (advisor)
The doctoral thesis deals with the use of convolutional neural networks for predicting the financial failure of companies. A bibliometric analysis was used during the processing of the literature review, which enabled a better orientation in scientific works oriented to the methods and approaches used in the past to predict the financial failure of companies. On the basis of the obtained knowledge, a deep learning model based on the GoogLeNet architecture was proposed, with inputs consisting of financial and macroeconomic indicators of companies. The modeling was based on the transfer learning method, in which it is possible to fine-tune the parameters of the pre-established networks to accelerate the learning process of the convolutional neural network. The initial set of financial and macroeconomic indicators was compiled from the variables that were most often used in business failure prediction models in scientific papers. Appropriate statistical methods were used for the specific selection of indicators from which the model is built. Since convolutional neural networks work best with image processing, the quantitative values of the input indicators were graphically interpreted and it was investigated which type of graphical processing is most suitable for predicting the failure of companies. Due to the existence of an unbalanced data set, the effect of the SMOTE method on the accuracy of the model's prediction was analyzed in the thesis. The method was used to increase the number of samples of the minority class of firms. To model the prediction of financial default, several variants of models were proposed, which differed in the form of input data. It was tested how the removal of outliers from the data set, the point in time from which the data come or the method of predictor selection will affect the accuracy of the prediction. The parameters of the resulting model were further fine-tuned so that it was able to classify businesses from new real data. The research conducted showed that using the right type of graphical processing of input data, SMOTE technique and appropriate parameter settings, convolutional neural networks can predict the financial failure of companies with high accuracy.
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Evaluation of Economy of Selected Non Profit Organization
Bartušková, Jana ; Šebestová, Monika (referee) ; Lajtkepová, Eva (advisor)
The bachelor thesis deals with the evaluation of the economy development of the selected nonprofit organization “Integrované centrum sociálních služeb Jihlava”, and that is for the period from 2017 to 2021. The aims and methods of the work are introduced at the beginning of the thesis. The theoretical part defines the basic concepts for the processing of the analytical part. The analytical part deals with the description of the selected organization, and the analysis of the costs, revenues and selected indicators of modified financial analysis. The proposals for the organization are presented in the conclusion.
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Evaluation of Economy and Fundraising of Selected Non Profit Organization
Štraubová, Veronika ; Šebestová, Monika (referee) ; Lajtkepová, Eva (advisor)
The bachelor thesis focuses on economic evaluation and fundraising activities of selected non-governmental non-profit organization called Dobrovolnické centrum Kladno.In the theoretical part of the bachelor's thesis there is a description of the issues of the non-profit sector and fundraising which is presented on the basis of selected literature. In the analytical part of the bachelor's thesis there is an analysis of costs and revenues and modified financial analysis. Based on these analyses there is a summary of development of the economy and fundraising. The last part of the bachelor's thesis is dedicated to own proposals for improving weaknesses.
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Using Artificial Intelligence to Reduce Risk in a Company
Friedl, Pavel ; Šebestová, Monika (referee) ; Dostál, Petr (advisor)
Presented diploma thesis is focused on evaluation of the supplier’s risk and the selection of the most suitable supplier with the use of artificial intelligence. The main part of the diploma thesis deals with the creation of the decision models. The decision models will be created in MS Excel and MATLAB based on the rules of the fuzzy logic. These models will determine the most suitable supplier for the company expert Elektro GOLA s.r.o. and they will also evaluate the supplier’s risk.
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