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Mathematical Modeling of Company Efficiency Using Neural Networks in Maple
Bartulec, Tomasz ; Vašátko, Jiří (referee) ; Chvátalová, Zuzana (advisor)
The goal of this thesis is to study the possibilities of Artificial neural network as an innovative mathematical methods for financial analysis of company performance, to find out what are today´s requests for performance evaluation of companies are and to identify possible ways how to use this relatively new concept in this area. When processing the possibilities of the computer program Maple for mathematical calculations will be applied. Intermediate objectives are then acquainted with the basic principle on which the artificial neural networks works, to analyze the financial performance of specific company and evaluate potential predictive abilities of the proposed network. The result of the work should be evaluating the success of this approach to financial analysis and evaluation of its use in practice.
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Measuring the Performance of a selected Company
Šimonová, Jana ; Kozáková, Petra (advisor) ; Hodulíková, Kateřina (referee)
The goal of the Diploma thesis is to evaluate with using modern performance measuring tools financial stability of B:TECH company and compare the results with the results of the traditional methods used by the company and suggest a concrete solution of established facts. To achieve this aim are used modern performance measuring tools based on value creation. Among them, there are Economic Value Added, RONA, CROGA, CFROI and DCF. The part of submitted thesis is also evaluation of the current system of measuring the performance of the selected company and its comparison with results of modern methods. The Company is currently using the methods based on Earnings before Interest and Taxes and a turnover. To choose the most suitable measuring tool was designed a benchmark matrix of used measuring tools. The most suitable measuring tools are selected Economic Value Added and RONA, which are considered to be the most useful for current measuring the performance in the Company.
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Mathematical Modeling of Company Efficiency Using Neural Networks in Maple
Bartulec, Tomasz ; Vašátko, Jiří (referee) ; Chvátalová, Zuzana (advisor)
The goal of this thesis is to study the possibilities of Artificial neural network as an innovative mathematical methods for financial analysis of company performance, to find out what are today´s requests for performance evaluation of companies are and to identify possible ways how to use this relatively new concept in this area. When processing the possibilities of the computer program Maple for mathematical calculations will be applied. Intermediate objectives are then acquainted with the basic principle on which the artificial neural networks works, to analyze the financial performance of specific company and evaluate potential predictive abilities of the proposed network. The result of the work should be evaluating the success of this approach to financial analysis and evaluation of its use in practice.
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