Academic year2016/17
CourseCOMPUTER ENGINEERING
Code595II
Credits6
PeriodSemester 2
LanguageEnglish
| Modules | Area | Type | Hours | Teacher(s) |
| INTELLIGENT SYSTEMS | ING-INF/05 | LEZIONI | 60 | |
Programma non disponibile nella lingua selezionata
Knowledge
This course aims to offer students the opportunity to learn the basic concepts and models of computational intelligence, to have a thorough understanding of the associated computational techniques, such as artificial neural networks, fuzzy systems and genetic algorithms, and to know how to apply them to a wide variety of application areas.
The student who successfully completes the course will have the ability to use intelligent systems to tackle problems not well solved by traditional approaches to computing.
Assessment criteria of knowledge
During the oral exam the student must demonstrate knowledge of the basic concepts about intelligent systems and the ability to develop intelligent systems. The lab project consists in the design and implementation of an intelligent system to solve a particular problem.
Methods:
Further information:
Oral exam (50%) and lab project (50%).
Teaching methods
Delivery: face to face
Learning activities:
- attending lectures
- individual study
- group work
- Laboratory work
Attendance: Advised
Teaching methods:
Syllabus
Basic concepts of artificial neural networks. Perceptron. Multi-Layer Perceptrons. Back-propagation. Radial-Basis Function networks. Self-organizing feature maps.
Introduction to fuzzy set theory and Fuzzy Logic. Fuzzy rules. Approximate reasoning. Fuzzy rule-based systems.
Introduction to genetic algorithms. Selection. Crossover. Mutation.
Hybrid intelligent systems.
Modelling and problem solving with intelligent systems: regression, classification, clustering, forecasting, decision support, data mining, data fusion.
Bibliography
The teacher will provide lecture slides and handouts.
Updated: 14/11/2016 17:27
