A Study of Modelling Non-stationary Time Series Using Support Vector Machines with Fuzzy Segmentation Information

Összesen: 152 db Független hivatkozások száma: 176 db Kumulatív impakt faktor: 29.496 have been applied for the modeling and clustering purposes of the industrial systems. Describes a new approach; instead of attempting to model the operator's decision making process, this design strategy uses a fuzzy model of the process itself and imbeds this in a model-based control algorithm. There are many advanced modeling techniques such as white box modeling, black box modeling, fuzzy logic modeling etc. [1]. … Usually fuzzy systems are synthesized using two types of rules that differ in the consequent (THEN part) proposition form: Mamdani, or standard [4] and Takagi-Sugeno, or functional [1]. Note also that if α = 1, (7) is the local least squares method [10] and if α is very large, (7) performs the original approach of Nakoula. It, however, becomes difficult to obtain transparent as well as accurate TS systems because of the trade-off between these requirements in fuzzy logic systems [3] that can be quite drastic [4]. As the nomenclature of nonlinear dynamical model is based on the terminology used to categorize linear input-output models, it can be summarized by the general family [8]: …