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Reminder: NOVA PhD Course "Novel Optimization Methods for Economic Modelling" - Open for Applications

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    Shutterstock, SFIO CRACHO

The course will take place on 11-15 Dec. 2017 in Helsinki, Finland (distant participation is also possible).
Application deadline: 30 Sept. 2017.

The course is of 5 ECTS and is organised by University Lecturer Stefan Bäckman, University of Helsinki - Faculty of Agriculture and Forestry.

NOVA course information web page

Apply here

Course Description
Are you working with optimization problems in economic modelling and lacking tools for finding the global optima instead of local optima? This course focuses on novel evolutionary optimization methods, such as genetic, memetic and bacterial-memetic algorithms, which are the cutting-edge methods to provide additional tools for evolutionary optimization and for finding the global optima. You will learn about these methods from Prof. László Kóczy (Széchenyi István University in Győr, Hungary), who is one of the globe’s leading scholars in this field, and Adj. Prof. Vesa Niskanen (University of Helsinki, Finland), who has a long international career in computational intelligence.

The course provides lectures and exercises in computer environment (using Matlab, Excel and R softwares). The methods are studied both from theoretical and practical standpoints, and applied in e.g. regression and time series analysis. The course is excellent for PhD students in economics and working with especially agricultural-related research questions, but beneficial also for other research fields.

The lectures are held at the University of Helsinki Viikki Campus, but distant participation is also possible via Adobe Connection online conference system.

Background
The traditional optimization methods have certain limitations. For example, it is typical for them that they can only provide local optima. They also often presuppose such mathematical features as continuity and differentiability for their optimizing functions. Novel evolutionary optimization methods can find the global optima in optimization. They are also more robust concerning the mathematical restrictions and thus more applicable in this respect.

In particular, the course considers such evolutionary computing methods as genetic, memetic and bacterial-memetic algorithms. In the course, we apply these methods to economic model construction and simulations in computer environment. We also use these methods within regression and time series models and cluster analysis. Hence, economical modelling is studied from both the theoretical and practical standpoints. Cognitive map modelling for examining very complex economic phenomena is also studied. Corresponding traditional mathematical and statistical methods are considered to some extent for the sake of comparison.

Prof. László Kóczy has a distinguished career in computational intelligence being also one of the leading scholars in computational intelligence and optimization with evolutionary computing. Adjunct. Prof. Vesa A. Niskanen has a long international career within computational intelligence, esp. in studies of fuzzy, neuro-fuzzy and genetic-fuzzy systems as well as in cognitive maps.

In autumn 2016 a related NOVA course “Introduction to economic modelling with computational intelligence (CI)”, arranged in the University of Helsinki, focused on computational intelligence methods. This course received positive and grateful feedback and inspired to apply for continuation. The upcoming NOVA PhD course “Novel Evolutionary Optimization Methods for Economic Modeling” can be regarded as a continuation for the previous economic modelling course and wishes welcome both new and previous students to the course.

Programme Outline
The lectures will take place in computer class 155A in Viikki Campus at the University of Helsinki, on 11-15 December 2017, daily from 10 AM to 1 PM.

In the first two lecture days, Monday and Tuesday, Adj. Prof. Niskanen and Dr. Antti Hyvärinen will provide an overview of economical modelling applications with optimization by using traditional and certain artificial intelligence (AI) methods: fuzzy systems and neural networks.

On Wednesday and Thursday Prof. László Kóczy will briefly introduce theoretically traditional optimization methods and continue in detail with the genetic, memetic and bacterial memetic algorithms.

On Friday the contents of the course is summarized by Adj. Prof. Niskanen who will also provide guidance and instructions for drawing up the course report.

On Thursday after the lectures, the participants are welcomed to gather for the common lunch in a restaurant located in Viikki Campus. Lunch is offered by the course organizer.

Main Teachers

  • Adjunct Professor Vesa A. Niskanen, University of Helsinki
  • Professor Laszlo Koczy, Széchenyi István University, Hungary

Please find more information on the course, as well as on how to apply and to receive user rights for the University of Helsinki network during the course on the NOVA course information web page:
https://www.nmbu.no/en/students/nova/students/phd-courses/phd-2017/node/31468

Published 6. September 2017 - 13:35 - Updated 3. April 2018 - 14:52

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