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Query-Driven Context-Aware Workflow
Mates, Vojtěch ; Rábová, Ivana (oponent) ; Zendulka, Jaroslav (oponent) ; Hruška, Tomáš (vedoucí práce)
The thesis presents an architecture design of the business process management system which is able to adapt to the changing context of already running business processes. The architecture of a system is designed to change particular fragments of the processes according to the current context. Thus it enables managing and rescheduling of processes while using historical data in the search for optimal variant of process performance.
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FORMAL MODEL OF DECISION MAKING PROCESS FOR HIGH-FREQUENCY DATA PROCESSING
Zámečníková, Eva ; Rábová, Ivana (oponent) ; Šaloun, Petr (oponent) ; Kreslíková, Jitka (vedoucí práce)
This thesis deals with the issue of the processing of high-frequency time series. It primarily focuses on the design of algorithms and methods for support of predicting these data. The result of this work is a model supporting the decision-making process implemented into a complex platform. The model designs the method of formalization of business rules which describes the decision-making process. The designed model must meet the conditions of the robustness, scalability, real-time processing and econometrics requirements. The thesis summarizes the current knowledge and methodologies for the processing of high-frequency fnancial data which can be found on the stock exchange. The first part of the work describes the basic principles and approaches currently used in the processing of high-frequency data. The next part deals with the description of an appropriate complex event platform and is subsequently devoted to prediction and data processing itself, using the chosen platform. Emphasis is on selecting and editing a set of rules that controls the decision-making process. The newly designed method describes the set of rules by using matrix grammar. This grammar belongs to the grammars with regulated rewriting and thus it may control the data processing by the defning of the matrices.
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Rozpoznávání objektů pomocí evolučních metod
Lýsek, Jiří ; Škorpil, Vladislav (oponent) ; Rábová, Ivana (oponent) ; Šťastný, Jiří (vedoucí práce)
Tato práce pojednává o použití evolučních metod, konkrétně gramatické evoluce k rozpoznávání objektů v obraze. V práci jsou popsány principy rozpoznávání objektů a evoluční metody se zaměřením na gramatickou evoluci. Ve vlastní práci jsou navrženy metody pro tvorbu klasifikátorů pomocí gramatické evoluce a je navržen vhodný postup včetně návrhu výpočtu fitness funkce. Nakonec je představeno vytvořené vývojové a testovací prostředí v jazyce Java.
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FORMAL MODEL OF DECISION MAKING PROCESS FOR HIGH-FREQUENCY DATA PROCESSING
Zámečníková, Eva ; Rábová, Ivana (oponent) ; Šaloun, Petr (oponent) ; Kreslíková, Jitka (vedoucí práce)
This thesis deals with the issue of the processing of high-frequency time series. It primarily focuses on the design of algorithms and methods for support of predicting these data. The result of this work is a model supporting the decision-making process implemented into a complex platform. The model designs the method of formalization of business rules which describes the decision-making process. The designed model must meet the conditions of the robustness, scalability, real-time processing and econometrics requirements. The thesis summarizes the current knowledge and methodologies for the processing of high-frequency fnancial data which can be found on the stock exchange. The first part of the work describes the basic principles and approaches currently used in the processing of high-frequency data. The next part deals with the description of an appropriate complex event platform and is subsequently devoted to prediction and data processing itself, using the chosen platform. Emphasis is on selecting and editing a set of rules that controls the decision-making process. The newly designed method describes the set of rules by using matrix grammar. This grammar belongs to the grammars with regulated rewriting and thus it may control the data processing by the defning of the matrices.
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Query-Driven Context-Aware Workflow
Mates, Vojtěch ; Rábová, Ivana (oponent) ; Zendulka, Jaroslav (oponent) ; Hruška, Tomáš (vedoucí práce)
The thesis presents an architecture design of the business process management system which is able to adapt to the changing context of already running business processes. The architecture of a system is designed to change particular fragments of the processes according to the current context. Thus it enables managing and rescheduling of processes while using historical data in the search for optimal variant of process performance.
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|
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Rozpoznávání objektů pomocí evolučních metod
Lýsek, Jiří ; Škorpil, Vladislav (oponent) ; Rábová, Ivana (oponent) ; Šťastný, Jiří (vedoucí práce)
Tato práce pojednává o použití evolučních metod, konkrétně gramatické evoluce k rozpoznávání objektů v obraze. V práci jsou popsány principy rozpoznávání objektů a evoluční metody se zaměřením na gramatickou evoluci. Ve vlastní práci jsou navrženy metody pro tvorbu klasifikátorů pomocí gramatické evoluce a je navržen vhodný postup včetně návrhu výpočtu fitness funkce. Nakonec je představeno vytvořené vývojové a testovací prostředí v jazyce Java.
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