K2F - a novel framework for converting fuzzy cognitive maps into rule-based fuzzy inference systems

Authors:
Lars Krüger
Affiliations:
Institute of Applied Microelectronics and Computer Engineering, Rostock University, Rostock, Germany
Venue:
ICAISC'10 Proceedings of the 10th international conference on Artificial intelligence and soft computing: Part I
Year:
2010

Citing 5
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Abstract

This paper focuses on a novel methodological framework for converting a Fuzzy Cognitive Map into a network of rule-based Fuzzy Inference Systems. Furthermore, it allows to obtain a crisp value representing an arbitrary parameter of the complex system's model. This way the system provides a quantitative answer without employing an exact mathematical model. This paper also outlines a first possible application area: the valuation of investments in high-technology ventures. A field in which usually conventional quantitative and retrospective measures usually do not deliver satisfying results due to the complexity of future-oriented risk prognosis and the lack of quantitative data.