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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2018/2019

Expert Systems in Electrical Power Engineering

The course is not on the list Without time-table
Code Completion Credits Range Language
XP15EXE Z,ZK 4 2+2s Czech
Lecturer:
Tutor:
Supervisor:
Department of Electrical Power Engineering
Synopsis:

Data processing and evaluation. Expert systems in electrical power engineering and diagnostics of insulating systems. Application of rule-based expert systems and neural networks in electrical power engineering and diagnostics of insulating systems. Creation of expert systems for electrical power engineering and electro diagnostics.

Requirements:
Syllabus of lectures:

1. Evaluating systems with elements of artificial intelligence.

2. Planning and diagnostic expert systems.

3. Knowledge representation. Steering.

4. Indefinites and inference inaccuracy in expert systems.

5. Knowledge engineering.

6. Using of expert systems in electrical power engineering.

7. Rule-based expert systems. Frame-based expert systems.

8. Genetic algorithms. Fuzzy logic.

9. Neural networks. Structure and superior brain functions.

10. Distributed artificial intelligence.

11. Application of rule-based expert systems in electro diagnostics.

12. Application of neural networks in electro diagnostics.

13. Expert systems for patterns recognition.

14. Predication by the help of neural networks.

Syllabus of tutorials:

1. Data processing, testing and evaluation of input data.

2. Using of expert systems in electrical power engineering.

3. Using of expert systems in electro diagnostics of electrical machines and equipment.

4. Application of rule-based expert systems in electrical power engineering.

5. Application of frame-based expert systems and fuzzy logic for recognition.

6. Creation of rule-based expert systems.

7. Creation of rule-based expert system for electro diagnostic application.

8. Application of neural networks in electrical power engineering.

9. Application of neural networks in electro diagnostics.

10. Application of artificial intelligence for supervisory control of electricity supply system.

11. Expert systems for pattern recognition.

12. Predication by the help of neural networks.

13. Creation of neural network and teaching set. Teaching of neural network.

14. Creation of neural network for electro diagnostic application.

Study Objective:
Study materials:

1. Date C. J.: An Introduction to Database Systems. Addison Wesley, 1995.

2. Tjoa A. M.: Database and Expert Systems Applications. Springer, 1990.

3. Mařík V., Vlček T.: Expertní systém FEL-EXPERT verze 3.2. ČVUT Praha, 1991.

4. Mařík V., Štěpánková O., Lažanský J. a kol.: Umělá inteligence (1), (2). Academia, Praha 1993, 1997.

5. Vondrák I.: Umělá inteligence a neuronové sítě. VŠB-TU, Fakulta elektrotechniky a informatiky, Ostrava 1995.

6. Šnorek M., Jiřina M.: Neuronové sítě a neuropočítače. ČVUT, Praha 1996.

7. Pokorný M.: Umělá inteligence v modelování a řízení. BEN, Praha 1996.

8. Záliš K.: Částečné výboje v izolačních systémech elektrických strojů. Academia, Praha 2005.

Note:
Further information:
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2019-03-20
For updated information see http://bilakniha.cvut.cz/en/predmet11637704.html