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Implementation and testing of selected optimization methods for the parameter estimation of simulation models
Zapletal, Marek ; Matoušek, Radomil (referee) ; Grepl, Robert (advisor)
This thesis deals with design of appropriate optimization algorithms for purposes of newly developed tool Mechlab’s parameter estimation, which serves for parameter estimation of simulation models in Matlab/Simulink. Levenberg-Marquardt algorithm had been chosen among other gradient methods. On the other hand, genetic algorithm and simulated annealing had been chosen from category of soft computing techniques to be implemented. Chosen algorithms were tested on artifical problem of mechanical oscilator and also on real datasets from electronic throttle. Proposed simulated annealing worked in both cases whith sufficient results, nevertheless was time-costly. For the oscilator problem, all the algorithms provided accurate solutions, but in the case of real dataset, Levenberg-Marquardt functionality was limited, while genetic algorithm still provided excelent results.
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Optimization of concrete structures using stochastic optimization methods
Slowik, Ondřej ; Pukl,, Radomír (referee) ; Novák, Drahomír (advisor)
The thesis focuses the reader on the sense of optimization and its importance for civil engineering. It outlines the principles used by some optimization methods and discusses the possibility of combination of any type of methods LHS with other optimization method. The result is a new type of optimization method named Nested LHS described in the text of the third chapter. The fifth chapter applies some of the lessons learned to solve practical optimization problem - reinforced concrete bridge solved by nonlinear finite element analysis using pseudostochastic optimization method LHS mean.
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Graphic Animation of Problem Solving Methods
Macek, Jiří ; Jurka, Pavel (referee) ; Zbořil, František (advisor)
There are many kinds of implementation artificial intelligence for automatic solving problems by computer technology. The main topics of this bachelor's thesis are some typical methods, describing of their features, comparing them among and shows some useful techniques of algoritmization and implementation too. Main purpose of this thesis is creating application, which clearly demonstrates at chosen problems methods of their solving.
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Shopping Advisor
Kocourek, Jakub ; Bartík, Vladimír (referee) ; Kolář, Dušan (advisor)
The attached bachelor thesis deals with nding the shortest ways in a shop for the selected purchase. The different technologies of creating web pages are described. As for the state space search algorithms are given for nding the shortest path between two points and for solving the travel salesmen problem. The thesis continues with the description of a design and implementation of application with all used technologies (PHP, Nette, MySQL, JS, JQuery) applying the Dijkstra's algorithm for nding the shortest path and genetic algorithm for solving the travel salesmen problem.
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Optimization Methods for SIMLIB/C++
Godula, Martin ; Martinek, David (referee) ; Peringer, Petr (advisor)
Bachelor's thesis is concerned with methods for global optimization. It deals with concept of optimization theoretically, and describes its goals and chosen optimization methods, suggests process of their implementation with regard to compatibility with simulation library SIMLIB/C++. It describes their implementation in C++ language and demostrates their functionality on different test problems and evaluates their rate of success.
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Traveling Salesman Problem: Parallel Methods Using SMP (Threads)
Weigner, Martin ; Jaroš, Jiří (referee) ; Kašpárek, Tomáš (advisor)
This thesis is focused on solving the problem of traveling salesman. At first, the problem is solved by serial access at four algorithms. There are two of them chosen and transferred to parallel access. In the end there are summarized observations about different parameters of both access. This thesis also introduces questions of programming parallel applications with threads to the reader.
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Prediction of Multiple Time Series at Stock Market Trading
Palček, Peter ; Zbořil, František (referee) ; Rozman, Jaroslav (advisor)
The diploma thesis comprises of a general approach used to predict the time series, their categorization, basic characteristics and basic statistical methods for their prediction. Neural networks are also mentioned and their categorization with regards to the suitability for prediction of time series. A program for the prediction of the progress of multiple time series in stock market is designed and implemented, and it's based on a model of flexible neuron tree, whose structure is optimized using immune programming and parameters using a modified version of simulated annealing or particle swarm optimization. Firstly, the program is tested on its ability to predict simple time series and then on its ability to predict multiple time series.
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