545-0938/01 – Classification and Expert Systems (KES)
| Gurantor department | Department of Economics and Control Systems | Credits | 10 |
| Subject guarantor | prof. Ing. Juraj Spalek, PhD. | Subject version guarantor | prof. Ing. Juraj Spalek, PhD. |
| Study level | postgraduate | Requirement | Choice-compulsory |
| Year | | Semester | winter + summer |
| | Study language | Czech |
| Year of introduction | 2016/2017 | Year of cancellation | 2022/2023 |
| Intended for the faculties | HGF | Intended for study types | Doctoral |
Subject aims expressed by acquired skills and competences
Introduction to basic methods used for classification and expert systems. Definition and description of input data that can be used to create an expert system. Furthermore, the basic realization of expert system using classification methods and application of technical problems
Teaching methods
Individual consultations
Summary
After an introductory section will discuss the basic concepts. It will be followed by an overview of classification methods describing their options and practical use. Furthermore, the basic architecture of an expert system will be discribed with an example of a simple implementation, which will eventually be supplemented by a classification system.
Compulsory literature:
A. Kidd, Knowledge Acquisition for Expert Systems: A Practical Handbook, 2012, e-ISBN-13: 978-1-4316-1823-1;
S.J. Russell and P. Norvig, Artificial Intelligence: A Modern Approach (2nd ed), Prentice-Hall, 2002. (1132 s.) ISBN-10: 0137903952, ISBN-13: 9780137903955
Recommended literature:
J. Pearl: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference (Paperback). Morgan Kaufmann, 1998 (552 s.) ISBN-10: 1558604790, ISBN-13: 978-1558604797
Additional study materials
Way of continuous check of knowledge in the course of semester
Studenti prokazují své dovednosti zpracováním semestrálního projektu popisující vybranou část řídícího procesu či problému, kde by aplikovali získané znalosti. Tuto práci studenti musí obhájit ústní formou, tak aby byli schopni jednoznačné definovat své požadavky, které má případně realizovat jiný subjekt (například realizační firma).
E-learning
Podpora priebežnej formy štúdia počas semestra využívaním elektronickej formy diseminácie prednášok a pomocných podkladov k jednotlivým témam podľa osnovy predmetu.
Other requirements
They will be specified at the beginning of the course.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1. The basic concepts
2. Overview of classification methods
3. Examples implementation of classification methods
4. Filtration input data
5. The basic architecture of expert systems
6. Use of classification methods in expert systems
7. Overview of selected implementation of expert systems used in practice
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
Předmět neobsahuje žádné hodnocení.