Database and Knowledge Systems (E371090)
Departments:ústav přístrojové a řídící techniky (12110)
Valid until: ??Range:2P+2C
Basic data models. Types and examples of database systems. Management of database systems. Design of database systems - examples. Programming techniques. Language SQL. Fundamentals of programming in database systems MS ACCESS.
Introduction in knowledge-based systems. Examples of applying knowledge-based systems in Engineering. Knowledge-based systems developed on principles of formal logic. Principles of Prolog. Knowledge-based systems with uncertainty calculus. Formal description of uncertainty. Fuzzy set theory. Computations with fuzzy sets. Linguistic approximation. Fuzzy logic. Types of fuzzy logic implications and inferences. Rule-based systems. Principles of Data-mining in databases. Expert systems - modular structure. Examples of expert systems: ETS, NEST, CLIPS, FEL-EXPERT, TRACER.
prof. Ing. Jiří Bíla DrSc.
Letní 2022/2023
Ing. Vladimír Hlaváč Ph.D.
Letní 2022/2023
prof. Ing. Jiří Bíla DrSc.
Letní 2021/2022
Ing. Vladimír Hlaváč Ph.D.
Letní 2021/2022
prof. Ing. Jiří Bíla DrSc.
Letní 2020/2021
Ing. Vladimír Hlaváč Ph.D.
Letní 2020/2021
P1. Introduction. General operations with information provided by data-base systems.
P2. E - R conceptual model. Limitations for relations defined in DBS.
P3. Models of Data-base System Management. Relational data-base systems. Codd
Characteristics (rules) for relational data-base systems. Set and relation operations in
relation data-base system.
P4. Architectures of Database System Management in personal computers. Systems
P5. Data-base application program languages. Structured language - SQL.
P6. Programming in the system MS Access.
P7. Programming in the system of SQL-type..
P8. Data-based and Knowledge-Based systems. Operations with knowledge. Decision and
Control paradigms. Operations with uncertainties. Theory of fuzzy sets.
P9. Operations with fuzzy sets. Fuzzy numbers and computing with fuzzy numbers.
Linguistic variable.
P10. Fuzzy logic. Compositional rule and fuzzy inference. Types of fuzzy implications and
their properties.
P11. Rule-based systems. (Examples.)
P12. Types and kinds of knowledge representation. Expert system - modular structure.
Inference engine and its co-operations with knowledge-base. System ETS.
P13. Expert systems - examples (FELExpert, TRACER, XCON/XSELL, KEE, NEST,
P14. Future of database and knowledge systems. Conclusions of lectures.
Structure of tutorial
C1. Fundamentals of work with Data-base systems.
C2. Data-based systems for non-programmers.
C3. Introduction in data-base system MS ACCESS. Realisation of set and relational
C4. Structured language - SQL. Assignment of semester tasks.
C5. Programming in MS ACCESS.
C6. Programming in data-base using SQL.
C7. Programming in data-base using SQL..
C8. Fuzzy numbers, computing with fuzzy numbers.
C9. Fuzzy logic. Compositional rule and fuzzy inference. Types of fuzzy implications and
their properties.
C10. Rule-based systems. Expert system ETS. Assignment of semester tasks.
C11. Expert system ETS - examples. Expert system NEST.
C12. Expert system NEST.
C13. Assistance and testing of results of semester tasks.
C14. Testing of semester tasks. Conclusion of the semester.
Databases, knowledge systems, rule based systems, expert systems, fuzzy logic, SQL
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