Parameter weighting for multi-dimensional fuzzy inference systems

Exponential growth of the number of rules of a multi-dimensional Fuzzy Inference System with growing number of input parameters makes it impractical for humans to populate the description of such a system via the Fuzzy Control Language by hand. In this paper we present a methodology for automatically generating rules. The generation process is influenced by a given weighting of the input parameters. The weighting is derived from a parameter weighting matrix used in the context of Analytic Hierarchy Process. The resulting Fuzzy Inference Systems are intended to be the starting point of an Adaptive Neuro-Fuzzy Inference System. As application of the methodology we present the security management at an airport. Here, Fuzzy Logic is used to evaluate the overall security situation.