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Fuzzy Markov chains and their use in risk management
Šindelková, Petra ; Vymazal, Tomáš (referee) ; Misák, Petr (advisor)
This thesis deals with the application of Markov chains for the production of concrete products. The theoretical part is focused on clarifying the concepts of risk management and describes the procedures for dealing with classical Markov chains. There are presented basics of fuzzy logic and finally there is explained the procedure using fuzzy logic in calculating of classical Markov chains in the subsection entitled Fuzzy Markov chains. The practical part describes production process, namely concrete pavements. On this production process is applied knowledge from the theoretical part and there is a comparison and evaluation of two methods of Marcov chains calculation (classic and fuzzy approach).
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Fuzzy logic methods for the risk assessment
Kovář, Kamil ; Vymazal, Tomáš (referee) ; Misák, Petr (advisor)
Master´s thesis deals about problematic of fuzzy logic, fuzzy sets and operation with them. Also thesis describing procedure of quantification risks through fuzzy sets, process of fuzzyfication, defuzzyfication a theirs application in the expert systems FMEA and FMECA. Using selected chapters of czech states standards are established critical areas in building process, it is a chapters about quality, safety and environment. With these areas by using fuzzy sets theory are created the procentual input values in the decision program, created by Matlab. Output from program is decision how big the risk rate is and if is necessarily make corrective measures. A concrete example is the production of concrete goods, describing production process and composition of fresh concrete. A practical example, created by using information from real company, is a decision about the risk rate in the qualitative area.
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The Application of Fuzzy Logic for Evaluation of Quality of Customers
Šulc, Ondřej ; Vítek, Pavel (referee) ; Dostál, Petr (advisor)
This master thesis deals with the application of fuzzy logic for evaluating the quality of customers in company PPL CZ s.r.o. For evaluation was used Microsoft Excel and MathWorks MATLAB. There are going to be created models using fuzzy logic. The introductory part is devoted to the theoretical bases that are necessary to understand the whole issue. The second part includes information about the company and analyzes of the current situation. Finally, the last part presents fuzzy models used to evaluation of existing customers.
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Using fuzzy clustering in modelling of hardened concrete properties
Haluska, Lukáš ; Vymazal, Tomáš (referee) ; Misák, Petr (advisor)
Compressive strength is one of the most monitored parameter of hardened concrete and it is usually determinated by destructive testing. Non-destructive testing applied on existing constructions uses regression analysis to estimate compressive strength. High variability of outputs and eventually failure of necessary requirements for using regression analysis complicate these methods. The aim of this thesis is to show posibility of using fuzzy clustering in this topic and to compare outputs with classic methods.
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Neural-Fuzzy Systems
Dalecký, Štěpán ; Samek, Jan (referee) ; Zbořil, František (advisor)
The thesis deals with artificial neural networks theory. Subsequently, fuzzy sets are being described and fuzzy logic is explained. The hybrid neuro-fuzzy system stemming from ANFIS system is designed on the basis of artificial neural networks, fuzzy sets and fuzzy logic. The upper-mentioned systems' functionality has been demonstrated on an inverted pendulum controlling problem. The three controllers have been designed for the controlling needs - the first one is on the basis of artificial neural networks, the second is a fuzzy one, and the third is based on ANFIS system. The thesis is aimed at comparing the described systems, which the controllers have been designed on the basis of, and evaluating the hybrid neuro-fuzzy system ANFIS contribution in comparison with particular theory solutions. Finally, some experiments with the systems are demonstrated and findings are assessed.
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Fuzzy Neural Networks
González, Marek ; Rozman, Jaroslav (referee) ; Zbořil, František (advisor)
This thesis focuses on fuzzy neural networks. The combination of the fuzzy logic and artificial neural networks leads to the development of more robust systems. These systems are used in various field of the research, such as artificial intelligence, machine learning and control theory. First, we provide a quick overview of underlying neural networks and fuzzy systems to explain fundamental ideas that form the basis of the fields, and follow with the introduction of the fuzzy neural network theory, classification and application. Then we describe a design and a realization of the fuzzy associative memory, as an example of these systems. Finally, we benchmark the realization using the pattern recognition and control tasks. The results are evaluated and compared against existing systems.
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