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Predikcia inflácie vybranými metódami strojového učenia
Číriová, Nora
The thesis is dealing with the assessment of how effective is the inflation forecast based on choosen indicators of inflation with the help of artificial intelligence in the Slovak Republic and the European Monetary Union. Specifically, it is about two methods of machine learning and those are the method of regression tree and the algorithm of nearest neighbors. Alignment of time series of inflation in the first part of the practical part is carried out by using current values of inflation factors. The second part is intended to equalising time series of inflation lagged values of these factors. Owing to the results we can select factors that have the greatest impact on the inflation.
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Aplikace dataminingových metod na bankovní data
Melichar, Miloš
The thesis deals with pre-processing of two data sets with information on clients, loans and debit cards. The data sets were separately pre-processed and modeled by SPSS Modeler using a number of methods and algorithms. For the modeling purposes, three classification data mining tasks were defined: loan approving or rejecting, loan rating and debit card type assignment. By using the selected methods of machine learning techniques the classification models were built for each task. Models accuracy was tested by script written in SPSS language for automation. All tasks were supplemented by clustering technique based on latent factors gained by factor analysis. Factor analysis combined with clustering presents another approach in pattern discovery.
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Artificial Intelligence and Industry 4.0
Hirsch, Radim ; Kroupa, Jiří (referee) ; Kovář, Jiří (advisor)
The aim of this work is to provide an overview of the application of artificial intelligence methods in the context of Industry 4.0. The first chapter defines the concept of industry 4.0, previous development of the industry and inclusion of the scientific field of artificial intelligence in this concept. The second chapter is focused on the applications of artificial intelligence methods in the field of machining, manufacturing industry, automation and energetics. The work concludes with evaluation of methods, their advantages and disadvantages from the point of view of individual practical applications and mentions possible directions of future development.
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Artificial Intelligence and Industry 4.0
Hirsch, Radim ; Kroupa, Jiří (referee) ; Kovář, Jiří (advisor)
The aim of this work is to provide an overview of the application of artificial intelligence methods in the context of Industry 4.0. The first chapter defines the concept of industry 4.0, previous development of the industry and inclusion of the scientific field of artificial intelligence in this concept. The second chapter is focused on the applications of artificial intelligence methods in the field of machining, manufacturing industry, automation and energetics. The work concludes with evaluation of methods, their advantages and disadvantages from the point of view of individual practical applications and mentions possible directions of future development.
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