Soft Computing

Welcome to the homepage of the course on Fuzzy Logic, Neural Network and Evolutionary Computation. This course intends to give a short introduction to so-called ‘soft computing,’ i.e., fuzzy logic, neural networks, their hybrid, neurofuzzy systems and Evolutionary methods. The intention of the course is to give the students an insight into the usage of fuzzy logic, fuzzy inferences systems, and learning systems for classification, without going into too much mathematical detail.

Course References
1 Li Xin Wang, A Course in Fuzzy Systems and Control, Prentice Hall, 1997.
Course Topics
1  Fuzzy Logic (FL),
2  Artificial Neural Networks (ANN),
3  Evolutionary Computation (EC),
4 Swarm Intelligence (i.e. Ant colony optimization and Particle swarm optimization, )
5 Additionally Some Machine Learning (ML) and Probabilistic Reasoning (PR) areas.
Read & Discuss these Papers:
#1 Paper Presentation
#2 Paper Presentation
 Exams and Practices
Reading List Papers and Book Chapters
Course Evaluation
Each Exercise = +0.5
* Paper Presentation = 2 / 20
* Final Exam = 14 / 20
* Take Home and Represent as Paper Format = 3 / 20
Conference Paper = 2 / 20 (+1)