Artificial Intelligence and Neural Networks

Lecturer:

Tutor:

Synopsis:

Formal apparatus of selected topics on Artificial Intelligence (Common Algebra, Formal Logic, Resolution Principle, Fuzzy Sets, Fuzzy Relational Calculus, Fuzzy Logic, Qualitative Algebras).

Qualitative modeling and system simulations. Fuzzy controllers, theory of design of fuzzy controllers, fuzzy controllers by Mamdani and Sugeno. Implementation of fuzzy controllers in the MATLAB/Simulink environment and Fuzzy Toolbox for MATLAB. Examples and applications. Qualitative methods in systems for fault detection. Expert systems and their applications to engineering problems. Neural networks. Classification of neural networks. MLP (Multi-Layer Perceptron) and RBF (Radial Basis Function) neural networks. Implementation of the neural networks in MATLAB/Simulink and the Neural Network Toolbox for MATLAB. Examples and applications.

Requirements:

in the scope of lectures

Syllabus of lectures:

P1. Mathematics for Artificial Intelligence.

P2. Mathematics for Artificial Intelligence.

P3. Formal and Software means for Problem Solving.

P4. Pattern Recognition. (Feature and geometric approach.)

P5. Pattern Recognition. (Structural approach.)

P6. Fuzzy and fuzzy-qualitative modelling and control.

P7. Fuzzy and fuzzy-qualitative modelling and control. (Fuzzy toolbox for MatLab/Simulink.)

P8. Neural Networks. (Introduction, MLP and RBF networks.)

P9. Higher Order Neural Networks Units (HONNU).

P10. Neural Networks. (Neural Network Toolbox for MatLab/Simulink.)

P11. Genetic algorithms. (Introduction and Classic GA.)

P12. Emergent problems.

P13. Application: Cardio-vascular system. Analysis and modelling, (HRV, EKG).

P14. Application: Diagnostics of structural and operation faults of constructions and systems.

Syllabus of tutorials:

C1. Mathematics for Artificial Intelligence

C2. Mathematics for Artificial Intelligence

C3. Fractal Dimension in Artificial Intelligence.

C4. Pattern Recognition. (Feature and geometric approach.)

C5. Pattern Recognition. (Structural approach.)

C6. Fuzzy a fuzzy-qualitative modelling and control.

C7. Fuzzy a fuzzy-qualitative modelling and control. (Fuzzy toolbox MatLab/Simulink.)

C8. Neural Networks . (MLP and RBF Networks.)

C9. Higher Order Neural Networks Units (HONNU).

C10. Genetic algorithms.

C11. Evolutionary algorithms.

C12. Emergent problems.

C13. Application: Cardio-vascular system. Analysis and modelling, (HRV, EKG).

C14. Application: Diagnostics of structural and operation faults of constructions and systems.

Study Objective:

Study materials:

1.P.H. Winston: Artificial Intelligence. Addison-Wesley Publishing Company, Amsterdam, 1977., 2.R.B. Banerji: Artificial Intelligence.(Theoretical Approach.) North Holland, N.Y., 1986., 3.B. Souček: Fuzzy, Holographic and Parallel Intelligence. John Wiley, N.Y., 1992.

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans: