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National Repository of Grey Literature 3 records found  Search took 0.01 seconds. 
Solution of complex problems using evolutionary algorithms
 Belovič, Boris ; Atassi, Hicham (referee) ; Burget, Radim (advisor)
Difficult problems are tasks which number of possible solutions increase exponentially or factorially. Application of common mathematical methods for finding proper solution in polynomial time is ineffective. Signal prediction is an example of diffucult problem. Signal is represented with a time serie and there is no explicit mathematical formula describing the signal. When genetic algorithms are applicated, they try to discover hidden patterns in time serie. These patterns can be used for prediction. Implication rules are used for discovery of these hidden patterns in time serie. Each rule is represented by one chromosome in population. Rules consist of two parts: conditional part and result part. Rules in population are compared with time serie and then the rules are evaluated according to their success in prediction. After the evaluation of rules, simulated evolution is started. Result of this evolution process is a group of rules which represent the most distinct patterns in time serie. These rules are then validated on validation set. Application is implemented in JAVA programming language.
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BI Open Source tools selection for small company
 Sukdol, Lukáš ; Šedivá, Zuzana (advisor) ; Pour, Jan (referee)
The master thesis deals with a theme of Open Source Business Intelligence tools from the point of view of a small company. The theoretical part describes the historical background of Open Source software and Business Intelligence theory. The practical part summarizes possibilities and properties of particular selected tools, based on implementation of partial activities with fi?ctional company data. Based on a multicriterial analysis, a variant proposal of BI solution for a specifi?c small company is created at the end of the thesis.
Detailed record
Solution of complex problems using evolutionary algorithms
 Belovič, Boris ; Atassi, Hicham (referee) ; Burget, Radim (advisor)
Difficult problems are tasks which number of possible solutions increase exponentially or factorially. Application of common mathematical methods for finding proper solution in polynomial time is ineffective. Signal prediction is an example of diffucult problem. Signal is represented with a time serie and there is no explicit mathematical formula describing the signal. When genetic algorithms are applicated, they try to discover hidden patterns in time serie. These patterns can be used for prediction. Implication rules are used for discovery of these hidden patterns in time serie. Each rule is represented by one chromosome in population. Rules consist of two parts: conditional part and result part. Rules in population are compared with time serie and then the rules are evaluated according to their success in prediction. After the evaluation of rules, simulated evolution is started. Result of this evolution process is a group of rules which represent the most distinct patterns in time serie. These rules are then validated on validation set. Application is implemented in JAVA programming language.
Detailed record

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