Abstract Fuzzy model identification is an effective tool for the approx-imation of uncertain
nonlinear systems on the basis of measured data. The identification of a fuzzy model using …

A methodology for the development of linguistically interpretable fuzzy models from data is
presented. The implementation of the model is conducted through the training of a neuro …

Разработки «умных» компьютеров начались более полувека назад. Однако вскоре
эйфория от первых успехов: математической модели нейрона, первых экспертных …

This article addresses the issue of outlier detection in industrial data using robust
multivariate techniques and soft sensing of clinker quality in cement industries. Feed-forward …

A novel fault tree analysis (FTA) technique based on the Takagi and Sugeno (T–S) model is
proposed in this paper. In the proposed technique, referred to as the TS-FTA, the events in …

This paper addresses the identification and control of nonlinear systems by means of Fuzzy
Hammerstein (FH) models, which consist of a static fuzzy model connected in series with a …

A novel framework for fuzzy modeling and model-based control design is described. The
fuzzy model is of the Takagi-Sugeno (TS) type with constant consequents. It uses …

In this paper, a modeling technique based on fuzzy system is used to predict the heat
transfer coefficient in pool boiling of distilled water. To achieve this, an experimental …

The capabilities of atmospheric gasoil as a feedstock of steam crackers were determined
through several experiments in a pilot plant. The operating variables that were considered in …

The rapid development of numerical modeling techniques has led to more accurate results
in modeling metal solidification processes. In this study, the cellular automaton-finite …