Topics for PhD Theses

  • Mathematical Fuzzy Logic
    (Petr Hájek, Petr Cintula, Rostislav Horčík, Libor Běhounek, Zuzana Haniková)
  • Alternative Mathematical Models for Uncertainty Quantification and Processing
    (Ivan Kramosil)
  • Super-Turing Computational Models
    (Jiří Wiedermann)
    The topic is focused on research of computational models which are computationally more powerful than Turing machines. Examples of such models include evolutionary interactive systems, amorphous computing, relativistic computing etc.
  • Classification Trees and Forests
    (Petr Savický)
    Classification trees and their ensembles, which are called classification forests, are a suitable method of a prediction of an unknown class on the basis of known attributes for complex distributions, if a sufficient amount of training cases is available. The typical methods of this type are CART, C4.5, Random Forests. The goal of the work is to investigate the properties of the methods and their modifications.
  • Complexity Measures of Neural Networks
    (Jiří Šíma) 
  • Spiking Networks Learning
    (Jiří Šíma)  
  • Generalization in neural-network learning
    (Věra Kůrková)
    The goal of the work is theoretical and experimental comparison of various approaches to generalization in neural network learning. For example, generalization modelled using various types of regularization and generalization based on output-weight minimization.
  • Modern Methods of Evolutionary Optimization
    (Martin Holeňa)
  • Modern Regression Methods
    (Martin Holeňa)
  • Modular Ontologies in the Semantic Web
    (Július Štuller) 
  • Database Topics
    (Július Štuller)
    Database Integration and Inconsistencies (Discovery, Removal and Tools)
    Data Integration by Intelligent Agents
    Database Visualization (Query Results Visualization, Datamining Visualization Methods, etc.)
    Databases with Imprecise Data (Models, Operators, Probability, Fuzzy and other Approaches, etc.)
    WWW Databases
    Multimedia Data and Databases