Fuzzy c-means (FCM) clustering is based on minimizing the fuzzy within cluster scatter matrix trace but FCM neglects the between cluster scatter matrix trace that controls the distances between the class centroids. Based on the principle of cluster centers separation, fuzzy cluster centers separation (FCCS) clustering is an extended fuzzy c-means (FCM) clustering algorithm. FCCS attaches import...

Cluster validation is an important issue in fuzzy clustering research and many validity measures, most of which are motivated by intuitive justification considering geometrical features, have been developed. This paper proposes a new validation approach, which evaluates the validity degree of cluster partitions from the view point of the optimality of objective functions in FCM-type clustering....

In this paper, we introduce the concept of complex multi-fuzzy sets (CMkFSs) as a generalization of the concept of multi-fuzzy sets by adding the phase term to the definition of multi-fuzzy sets. In other words, we extend the range of multi-membership function from the interval [0,1] to unit circle in the complex plane. The novelty of CMkFSs lies in the ability of complex multimembership functi...

Possibilistic logic in general [7, 8, 9, 10] investigates how possibilistic uncertainty about propositions is propagated when making inferences in a formal logical system. In this paper, we look at a very particular aspect of possibilistic logic: we investigate how, under certain independence assumptions, the introduction of possibilistic uncertainty in classical propositional logic leads to th...

In this paper, a new interval-valued fuzzy multi-criteria group decision-making model is proposed to evaluate each of the energy plans with sustainable development criteria for proper energy plan selection. The purpose of this study is divided into two parts: first, it is aimed at determining the weights of evaluation criteria for sustainable energy planning and second at rating sustainable ene...

COVID-19's developing trend has put the waste management systems of governments all over world in jeopardy. The increasing rise infectious medical now become a serious problem. This paper presents multi-period multi-objective model for designing system during COVID-19 pandemic. aims to reduce total costs while also reducing environmental impact treatment centers, disposal and transportation. It...

Possibilistic fuzzy c-means (PFCM) is one of the most widely used clustering algorithm that solves noise sensitivity problem Fuzzy (FCM) and coincident clusters possibilistic (PCM). Though PFCM a highly reliable but efficiency can be further improved by introducing concept suppression. Suppression-based algorithms employ winner non-winner based suppression technique on datasets, helping in perf...

The structure of Chinese characters is reviewed and seen to be best represented as a 3-layer hierarchy of character, radical and stroke. Fuzzy possibilistic reasoning is then put forward as an appropriate set of conceptual tools to investigate the automatic recognition of these characters. Associative memory artificial neural network algorithms form a suitable technique for realising these conc...

Statistical distribution of language structures reflect important regularities controlling informational and psycho-physiological processes, which accompany the generation of verbal language or printed texts. In this paper, fuzzy quantitative models of language statistics are constructed. The suggested models are based on the assumption about a super-position of two kinds of uncertainties: prob...

Possibilistic states of information are fuzzy sets of possible worlds. They constitute a complete lattice, which can be endowed with a monoidal operation (a t-norm) to produce a quantal. An algebraic semantics is presented which links possibilistic formulae with information states, and gives a natural interpretation of logical connectives as operations on fuzzy sets. Due to the quantal structur...