The design methodology is based on fuzzy clustering methods for partitioning the input-output space combined with genetic algorithms (GA), and recursive least-squares (LS) optimization methods for model parameter adaptation.
Two algorithms based on fuzzy simulation methods and Genetic Algorithm are developed for these two models.
This allows to develop a global model based on fuzzy clustering method using algorithms based on fuzzy inference systems for classification of real data of the examined gas turbine.
Furthermore, based on fuzzy approximation method, the circuit design procedure for robust stability and noise filtering of a nonlinear stochastic gene network with process delay could be simplified from the linear gene network design point of view.
However, based on fuzzy approximation method, the nonlinear stochastic gene network with time delays is approximated by interpolating several local linear systems with time delays at different operation points.
In [20 22], visual information has been used to develop safety strategies based on fuzzy logic, probabilistic methods, or the calculation of warning index, respectively.
In this research work, a novel framework for the construction of augmented Fuzzy Cognitive Maps based on Fuzzy Rule-Extraction methods for decisions in medical informatics is investigated.
After that, we present a distributed implementation of the clustering algorithm based on fuzzy C-means method.
