Intelligent Systems for Decision Support
Code
10612
Academic unit
Faculdade de Ciências e Tecnologia
Department
Departamento de Engenharia Mecânica e Industrial
Credits
3.0
Teacher in charge
Isabel Maria Nascimento Lopes Nunes
Weekly hours
3
Total hours
50
Teaching language
Português
Objectives
The aim of this course is to teach students the theoretical foundations of artificial intelligence, systems architecture and the main approaches used in intelligent systems. Particular emphasis is given to the basic principles of approximate reasoning based on fuzzy logic and its application to modeling, control and decision making, combining qualitative and quantitative data. The case studies reflect situations of decision making in uncertain and/or complex environments in the context of Industrial Engineering.
Prerequisites
Not required.
Subject matter
1. Introduction to Artificial Intelligence
2. Decision support systems and Expert systems
a. Architecture
b. Knowledge Engineering Methods
c. Inference processes
3. Description of the main approaches (eg, fuzzy logic, multicriteria methods, heuristic methods)
4. Approximate Reasoning based on Fuzzy Logic
5. Fuzzy Multicriteria Decision Making
6. Applications in Industrial Engineering
Bibliography
- Gupta, J. N. D., G. A. Forgionne, Mora, M.T. (2010). Intelligent Decision-making Support Systems: Foundations, Applications and Challenges (Decision Engineering), Springer.
- Ross, T. J. (2010). Fuzzy Logic with Engineering Applications, John Wiley.
- Turban, E., R. Sharda, et al. (2010). Decision Support and Business Intelligence Systems, Prentice Hall.
- Sivanandam, S. N,. Deepa S. N., Sumathi S., Introduction to Fuzzy Using Matlab, Springer, 2007
- Zimmermann, H.-J. (2001). Fuzzy Set Theory and Its Applications, Kluwer Academic Publishers.
- Zadeh, L. A. (1965). "Fuzzy sets." Information and Control 8(3): 338-353.
Teaching method
Theoretical-practical classes with a duration of 3h. Oral presentation of concepts, supported by multimedia teaching materials and accompanied by application to concrete cases where students take part individually or in groups.
Evaluation method
The evaluation process has the following components:
- 1 practical project-assignment, with oral communication and with written technical report (TP) (40%)
- 2 mid-term written tests during the course (T 1, T 2) (60%)
Formula for the calculation of the final grade:
- Final Grade = 30%T 1 + 30%T 2 + 15%TP1+25%TP2
To succeed students must obtain:
(average(T 1; T 2) >= 10) AND (TP1; tp2 >= 10)
1 Exam (for student without approval in written tests).