Associate professor in the department of information science at the University of Bergen, Norway, from which he received his Ph.D. degree in informatics. Current research interests include system dynamics, uncertainty management, and machine learning.
Fuzzy system dynamics: An approach to vague and qualitative variables in simulation
Version of Record online: 26 DEC 2006
Copyright © 1994 John Wiley & Sons, Ltd.
System Dynamics Review
Volume 10, Issue 1, pages 49–62, Spring 1994
How to Cite
Tessem, B. and Davidsen, P. I. (1994), Fuzzy system dynamics: An approach to vague and qualitative variables in simulation. Syst. Dyn. Rev., 10: 49–62. doi: 10.1002/sdr.4260100104
- Issue online: 26 DEC 2006
- Version of Record online: 26 DEC 2006
- Manuscript Accepted: JUL 1993
- Manuscript Received: JAN 1993
The application of fuzzy numbers is suggested as an alternative to probabilistic methods for the management of uncertainty and vagueness in system dynamics models. Fuzzy numbers are particularly well suited for representing qualitative values and are used during simulation. To handle interaction among variables, we utilize global optimization methods. In nonlinear models, however, our implementation does not suffice. We illustrate the use of fuzzy numbers, qualitative values, and the problems of implementation by some simple examples.