Cluster-weighted modeling as a basis for fuzzy modeling

Cluster-weighted modeling (CWM) is emerging as a versatile tool for modeling dynamical systems. It is a mixture density estimator around local models. To be specific, the input regions together with output regions are treated to be Gaussian serving as local models. These models are linked by a linear or non-linear function involving the mixture of densities of local models. The present work shows a connection between the CWM and generalized fuzzy model (GFM) thus paving the way for utilizing the concepts of probability theory in the fuzzy domain that has already emerged as a versatile tool for solving problems in uncertain dynamic systems.