Subject: Advanced Intelligent Systems for Decision Support (17.IMDR17 )
Study programmes of the course:
| Type of studies | Title |
|---|---|
| Doctoral Academic Studies | Industrial Engineering / Engineering Management (Year: 1, Semester: Summer) |
The objective of the course is to master advanced knowledge in the field of intelligent decision-support systems (IDSS) in order to enable the student to independently carry out engineering data analysis during scientific research. The aim of the course is that a doctor of technical sciences from the field of Industrial Engineering and Management acquires competencies for the application of advanced computer intelligence tools in complex problems of decision making in production and service systems.
Students will be trained for research and development of advanced intelligent systems for decision support. Using artificial intelligence techniques, students will master methods of machine learning, data mining, and how to teach computers to think more like humans. A doctor of science in the field of Industrial Engineering and Management acquires competencies for the development and application of advanced intelligent systems for decision support.
Introduction. Deciding under conditions of uncertainty and imprecision. Fuzzy inference systems (FIS). Knowledge Based Systems. Expert systems. Self-learning systems. Predictive manufacturing systems. Flexible decision support systems. Smart manufacturing. Smart factory.
Teaching on the course includes lectures and exercises with examples of advanced intelligent decision support systems. During the semester the student is obliged to do a project where he will apply the acquired knowledge in the field of intelligent decision support systems. All lectures and research are carried out with computers and sophisticated software.
| Authors | Title | Year | Publisher | Language |
|---|---|---|---|---|
| 2017 | English | |||
| 2004 | English | |||
| 2006 | English | |||
| 2015 | English |
| Course activity | Pre-examination | Obligations | Number of points |
|---|---|---|---|
| Project | Yes | Yes | 40.00 |
| Oral part of the exam | No | Yes | 50.00 |
| Exercise attendance | Yes | Yes | 5.00 |
| Lecture attendance | Yes | Yes | 5.00 |
Assoc. Prof. Rikalović Aleksandar
Associate Professor
Lectures
Assoc. Prof. Rikalović Aleksandar
Associate Professor
Study research work
Faculty of Technical Sciences
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© 2024. Faculty of Technical Sciences.