This paper deals with multi-class classification for linguistic fuzzy rule based classification systems. The idea is to decompose the original data-set into binary classification problems using the pairwise learning approach (confronting all pair of classes), and to obtain an independent fuzzy system for each one of them. Along the inference process, each fuzzy rule based classification system ...

introduction drastic model is an index and overlapping model that has been designed for producing vulnerability scores for different points by combining several thematic layers. overlapping distinguished methods are themost applicable methods for evaluatingvulnerability of aquifers because they are cheap, they can directly reach a defined goal, the used data in the methods are accessible or can...

Since the proposal of Zadeh and Mamdani’s seminal ideas, interpretability is acknowledged as one of the most appreciated and valuable characteristics of fuzzy system identification methodologies. It represents the ability of fuzzy systems to formalize the behavior of a real system in a human understandable way. Interpretability analysis involves two main points of view: readability of the knowl...

This paper demonstrates different types support vector regression (SVR) for annealing robust fuzzy neural networks (ARFNNs) to identification of nonlinear magneto-rheological (MR) damper with outliers. A SVR has the good performances to determine the number of rule in the simplified fuzzy inference system and initial weights for the fuzzy neural networks. In this paper, we independently propose...

This paper reviews some important points of sparse rule-bases, the reason of their generation and after that three methods are presented, which allow the approximation of the missing rules with reasonable demand on computing. The delimitations and advantages of these methods are presented, too. Fuzzy systems based on a sparse rule-base do not have rules for all the possible combinations of obse...

In this paper we propose a propositional temporal language based on fuzzy temporal constraints which turns out to be expressive enough for domains –like many coming from medicine– where knowledge is of propositional nature and an explicit handling of time, imprecision and uncertainty are required. The language is provided with a natural possibilistic semantics to account for the uncertainty iss...

extended abstract 1. introduction human life is highly dependent on the environment and the services that are provided by the environment. environmental quality is a set of properties and characteristics of the environment, either generalized or local, as they may also impinge on human beings and other organisms. it is a measure of the condition of an environment relative to the requirements of...

Approximate fuzzy reasoning methods serves the task of inference in case of fuzzy systems built on sparse rule bases. This paper is a part of a longer survey that aims to provide a qualitative view through the various ideas and characteristics of interpolation based fuzzy reasoning methods. It also aims to define a general condition set for fuzzy rule interpolation methods brought together from...

This paper reviews some important points of sparse rule-bases, the reason of their generation and after that three methods are presented, which allow the approximation of the missing rules with reasonable demand on computing. The delimitations and advantages of these methods are presented, too. Fuzzy systems based on a sparse rule-base do not have rules for all the possible combinations of obse...