450-4049/05 – Applied Artificial Intelligence Methods (AUI)
| Gurantor department | Department of Cybernetics and Biomedical Engineering | Credits | 5 |
| Subject guarantor | prof. Ing. Martin Černý, Ph.D. | Subject version guarantor | prof. Ing. Martin Černý, Ph.D. |
| Study level | undergraduate or graduate | Requirement | Compulsory |
| Year | 1 | Semester | summer |
| | Study language | Czech |
| Year of introduction | 2022/2023 | Year of cancellation | |
| Intended for the faculties | EKF | Intended for study types | Follow-up Master |
Subject aims expressed by acquired skills and competences
The subject represents the introduction to the principles of scientific field of artificial intelligence. The goal of subject is introduce students on analysis and design of artificial intelligence tolls in the field of biomedical engineering.
Students will be ready for practical use of basic artificial intelligence tools namely fuzzy expert systems, artificial neural networks and genetic algorithms in the field of BME.
Teaching methods
Lectures
Tutorials
Experimental work in labs
Summary
Subject deals with gathering of knowledge and applications of the artificial intelligence methods in the context of processing and modeling of the biomedical image data. Subject is composed from four main areas of the artificial intelligence. The first part of the subject deals with the fuzzy mathematics, fuzzy modeling, and design of the expert systems. The second part of the subject deals with the data classification with emphasis to an area of the neural network. Next area deals with optimization techniques with emphasis of an analysis of the genetic algorithms for solving of the complex mathematical problems. The last part of the subject focuses to hierarchical and non-hierarchical methods of the cluster analysis.
Compulsory literature:
Recommended literature:
Way of continuous check of knowledge in the course of semester
Podmínky zápočtu: (celkem 40 bodů, minimum pro získání zápočtu 21)
20b Realizace fuzzy modelu (protokol nebo SW)
20b Vytvoření vlastního pravidlového systému v prostředí Clips
Podmínky vykonání zkoušky (celkem 60 bodů)
40 bodů písemná/praktická část - realizace fuzzy modelu nebo pravidlového systému v prostředí Clips dle zadání
20 bodů ústní zkouška na teoretické znalosti.
E-learning
Other requirements
Compulsory participation in seminars 80% of seminars.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
Lectures
1. Principles and methods of artificial intelligence. Methods of computer representation of knowledge and language modeling.
2. Basics of fuzzy mathematics and fuzzy logic.
3. Fuzzy expert systems.
4. Fuzzy models.
5. Methods for verifying the design of fuzzy models
6. Basics of graph theory, definitions, graph search methods, problem, state space
7. Introduction to knowledge systems - definition, brief history, applications
8. Architecture of knowledge systems, knowledge base and fact base
9. Inference mechanism
10. Problems of the "select" function, quantitative and qualitative heuristics
11. Other modules of knowledge systems
12. Introduction to knowledge engineering, life cycle of knowledge system
Computer exercises
1. Introduction to mathematical modeling in MATLAB.
2.Methodology of fuzzy model design in MATLAB environment
3. Design of a fuzzy model focused on economics
4. Debugging fuzzy custom fuzzy models
5. Presentation of created fuzzy models
6. Shell Expert System Clips - introduction to working with the system
7. Variable, definition of facts and rules
8. Lists
9. Working with facts
10. Lists and multivalued variables
11. Auxiliary facts and priority of rules
12. Templates, subsetp command
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
Předmět neobsahuje žádné hodnocení.