In this paper, a possibilistic disjunctive logic programming approach for modeling uncertain, incomplete and inconsistent information is defined. This approach introduces the use of possibilistic disjunctive clauses which are able to capture incomplete information and incomplete states of a knowledge base at the same time. By considering a possibilistic logic program as a possibilistic logic th...

Recently, a good set of logic programming semantics has been defined for capturing possibilistic logic program. Practically all of them follow a credulous reasoning approach. This means that given a possibilistic logic program one can infer a set of possibilistic models. However, sometimes it is desirable to associate just one possibilistic model to a given possibilistic logic program. One of t...

Inconsistent knowledge bases usually are regarded as an epistemic hell that have to be avoided at all costs. However, many times it is di cult or impossible to stay away of managing inconsistent knowledge bases. In this paper, we introduce an argumentation-based approach in order to manage inconsistent possibilistic knowledge bases. This approach will be exible enough for managing inconsistent ...

Elaborating an appropriate cellular manufacturing system (CMS) could solve many structural and operational issues. Thereby, considering some significant factors as worker skill, machine hardness, and product quality levels could assist the companies in current competitive environment. This paper proposes a novel interactive possibilistic mixed integer nonlinear approach to minimize the total co...

Possibilistic causal models have been proposed as an approach for prediction and diagnosis based on uncertain causal relations. However, the only way to develop the causal models is to acquire the possibilistic knowledge from the experts. The paper proposes an approach to develop the models from a dataset including causes and effects. It first develops a probabilistic causal model, then transfo...

The design of closed-loop supply chain networks has attracted increasing attention in recent decades with environmental concerns and commercial factors. Due to the rapid growth of knowledge and technology, the complexity of the supply chain operations is increasing daily and organizations are faced with numerous challenges and risks in their management. Most organizations with limited resources...

In this paper, a new approach for fault detection and isolation that is based on the possibilistic clustering algorithm is proposed. Fault detection and isolation (FDI) is shown here to be a pattern classification problem, which can be solved using clustering and classification techniques. A possibilistic clustering based approach is proposed here to address some of the shortcomings of the fuzz...

In 1987 Dubois and Prade defined an interval-valued expectation of fuzzy numbers, viewing them as consonant random sets. In 2001 Carlsson and Fullér defined an interval-valued mean value of fuzzy numbers, viewing them as possibility distributions, and they introduced the notation of crisp possibilistic mean value and crisp possibilistic variance of continuous possibility distributions, which ar...

This paper presents a latest survey of different technologies using fuzzy clustering algorithms. Clustering approach is widely used in biomedical field like image segmentation. A different methods are used for medical image segmentation like Improved Fuzzy C Means(IFCM), Possibilistic C Means(PCM),Fuzzy Possibilistic C Means(FPCM), Modified Fuzzy Possibilistic C Means(MFPCM) and Possibilistic F...