Planning resources for a supply chain is a major factor determining its success or failure. In this paper we introduce an Interval Type-2 Fuzzy Logic model of a distribution network. It is believed that the additional degree of uncertainty provided by Interval Type-2 Fuzzy Logic will allow for better representation of the uncertainty and vagueness present in resource planning models. First, the...

This work is focused on creating fuzzy granular classification models based on general type-2 fuzzy logic systems when consequents are represented by interval type-2 TSK linear functions. Due to the complexity of general type-2 TSK fuzzy logic systems, a hybrid learning approach is proposed, where the principle of justifiable granularity is heuristically used to define an amount of uncertainty ...

The Interval Type-2 Fuzzy Logic Controller (IT2FLC) for a Quadruple Tank Process (QTP) is demonstrated in this paper. Here the Interval Type-2 based Fuzzy membership function is used. The QTP is made to operate in minimum phase mode. The vertices of fuzzy membership functions are tuned with IT2FLC to minimize Integral Absolute Error. Performance of IT2FLC and Type-1 Fuzzy Logic Controller (T1FL...

image segmentation is an essential issue in image description and classification. currently, in many real applications, segmentation is still mainly manual or strongly supervised by a human expert, which makes it irreproducible and deteriorating. moreover, there are many uncertainties and vagueness in images, which crisp clustering and even type-1 fuzzy clustering could not handle. hence, type-...

In recent years, there have been a growing interest in developing Multi-Criteria Decision Making (MCDM) and Group Decision Making (GDM) using type-2 fuzzy sets and Intuitionistic Fuzzy Sets (IFSs) which provide frameworks to handle the encountered uncertainties in decision making models. Previous research has shown the power of type-2 fuzzy logic systems to handle the linguistic uncertainties. ...