Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6903936 | Applied Soft Computing | 2018 | 45 Pages |
Abstract
For about 50 years, fuzzy modelling methods have prevailed in the effective treatment of vagueness and uncertainty employing scientific and real-world applications. In this paper, we propose a modelling method using multidimensional fuzzy patterns based on parametric membership functions of the potential type. We outline methodological advantages, such as the preservation of the same highly flexible and efficient membership function type in one- and multidimensional modelling and fuzzy pattern classifier sequences. Furthermore, the model accounts for cognitive aspects of human reasoning, for instance, in knowledge organization and working memory processes. We argue that this methodology is particularly convenient for modelling issues in human-machine interactions and human sciences, such as medicine, and present two multidimensional fuzzy pattern models for infectious diseases.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Franziska Bocklisch, Daniel Hausmann,