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Computational Intelligence

Code 15642
Year 1
Semester S2
ECTS Credits 6
Workload PL(30H)/T(30H)
Scientific area Informatics
Entry requirements Does not have.
Learning outcomes The main goal of this CU is that the students acquire knowledge and competencies in the area of computational intelligence: they should master the models and language related to neural networks, evolutionary computation,swarm intelligence and fuzzy systems. They should be able to explain the key models and ideas in each of these areas and implement their main algorithms. They should also be able to solve problems using the methods from this CU.
Syllabus 1-Neural networks
1.1-The artificial neuron
1.2-Supervised learning
1.3-Practical issues regarding supervised learning
1.4-Unsupervised learning

2-Evolutionary computation
2.1-Genetic algorithms
2.2-Genetic programming
2.3-Evolutionary strategies

3-Swarm intelligence
3.1-Particle swarm optimization
3.2-Ant colony optimization

4-Fuzzy systems
4.1-Fuzzy systems
4.2-Fuzzy inference
4.3-Fuzzy control
Main Bibliography -Os PDFs das aulas teóricas elaborados pelo docente / The PDFs presented on the theoretical classes.
-James M. Keller, Derong Liu, David B. Fogel, Fundamentals of Computational Intelligence: Neural Networks, Fuzzy Systems, and Evolutionary Computation, 2016-
-Andries P. Engelbrecht, Computational Intelligence, An Introduction, John Wiley & Sons, 2007.
-J. Kennedy, R.C. Eberhart, Y. Shi, Swarm Intelligence, Morgan Kaufmann Publishers, 2001.
-Aboul Ella Hassanien, Eid Emary, Swarm Intelligence: Principles, Advances, and Applications, 2015
-Simon O. Haykin, Neural Networks and Learning Machines (3rd Edition), 2008
Teaching Methodologies and Assessment Criteria This CU has both theoretical and practical laboratory classes.
In the theoretical classes the teacher presents the syllabus topics and discusses them with the students.
In the practical classes the students solve proposed problems using the Python programming language.

The assessment is made using 2 theoretical tests and practical project.
The final grade is obtained considering 70% of the grade in the theoretical tests and 30% in the practical project.
The students can raise their grades by obtaining an improved result in a final exam.
Language Portuguese. Tutorial support is available in English.
Last updated on: 2024-03-04

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