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Lecturer(s)
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Hájek Petr, prof. Ing. Ph.D.
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Course content
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Artificial and computational intelligence. Synthesis and analysis of decision-making processes with uncertainty. Classification and prediction economic processes by fuzzy inference systems. Fuzzy inference systems. Models of neural networks, classification and prediction. Process learning in neural networks. Evolution stochastic optimization algorithms. Neuro-fuzzy-genetic systems. Computational intelligence in decision-making, control, classification and prediction. Ambient intelligence.
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Learning activities and teaching methods
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Methods of individual activities
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Learning outcomes
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The aim of the course is to provide basic knowledge in the area of artificial and computational intelligence (Soft Computing - fuzzy sets, neural networks, evolution stochastic optimization algorithms) and the possibilities for its use in various areas of social life, especially the economics, social and environmental fields. The students should be able to design neuro-fuzzy-genetic systems for classification, prediction and optimization processes.
The students should be able to design fuzzy inference systems for classification and prediction, especially in the economics, social and environmental spheres, as well as to design models based on neural and fuzzy neural networks.
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Prerequisites
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unspecified
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Assessment methods and criteria
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Discussion
Completion and successful defense of project from the field of dissertation work.
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Recommended literature
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GHOSH A., TSUTSUI S. Advances in Evolutionary Computing. Theory and Applications.. A Springer-Verlag Company, Germany, 2003.
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KUNCHEVA L. I. Fuzzy Classifier Design.. A Springer Verlag Company, Germany, 2000.
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KVASNIČKA V. a kol. Evolučné algoritmy.. STU, Bratislava, 2000.
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Kvasnička V. a kol. Úvod do teórie neurónových sietí. 1997, IRIS Bratislava.. IRIS, Bratislava, 1997.
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OLEJ V. Modelovanie ekonomických procesov na báze výpočtovej inteligencie.. Miloš Vognar - M&V, Hradec Králové, 2003. ISBN 80-903024-9-1.
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RUSSEL, S.-NORVIG, P. Artificial Intelligence. A Modern Approach. Prentice Hall. New Jersey, 2003.
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RUTKOWSKI L., KACPRZYK J. Advances in Soft Computing. Neural Networks and Soft Computing.. A Springer-Verlag Company, Germany, 2003.
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