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The course aims at providing basic knowledge and skills for constructing computer models with computational intelligence methods. Skills for economical applications in this area are also provided. To some extent, knowledge and skills of statistical modelling are empowered. A cutting-edge, multi-disciplinary approach to model construction will be adopted.
Computational intelligence (CI) generally includes such methods as neural networks, fuzzy systems, evolutionary computing, Bayesian networks, cellular automata and swarm theory. Today CI is applied to systems and models in control, decision making, pattern recognition, robotics, data mining, biological and social modelling and statistics, inter alia. In particular, they are useful when non-parametric or non-linear models are constructed, and they often yield better and simpler computer models than the corresponding classical mathematical models.
Many models and theoretical results of CI are already available in economics, but their application is still uncommon and fairly unfamiliar in the Nordic countries (possibly excluding Finland). Hence, there is a justified need for a course which deals with the basics and economical applications of CI.
Please find more information on the course on the University of Helsinki's course webpage.
The course focuses on fuzzy systems, neural networks and evolutionary computing. It presents the basic principles and economical applications of these methods in computer modelling. Corresponding traditional mathematical and statistical models are also considered. During the course days fuzzy rule-based economical computer models are designed and constructed, and they are fine-tuned with neural networks and genetic algorithms. Fuzzy cognitive maps, both numerical and linguistic, are also examined because these are simple and usable models for examining complex phenomena. CI models are compared to such corresponding traditional methods as regression, cluster, discriminant and time series analysis.
The course days include 4-5 hours of lectures, which can also be followed live with Adobe Acrobat connection. Lectures comprise of theory parts on computational intelligence and exercises on economical model constructions with Matlab.
Students can participate and complete the course from their home countries if they wish to. In that case they need to follow the lectures online with Adobe connection. The teacher has good experiences of this kind of teaching. Students are able to ask questions during the lectures via the programme.
- Adjunct Prof. Vesa Niskanen
- Patrik Eklund, University of Umeå
Please find more information on the course and on how to apply here: