Fuzzy Information and Engineering

Pedrycz, Witold

2015 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2015.03.001

AbstractIn the era of advanced methodologies and practices of system modeling, we are faced with ever growing challenges of building models of complex systems that are in full rapport with reality. These challenges are multifaceted. Human centricity becomes of paramount relevance in system modeling and because of this models need to be customized and easily interpretable. More and more visibly, experimental data and knowledge of varying quality being directly acquired from experts have to be efficiently utilized in the construction of models. The quality of data and ensuing quality of models have to be prudently quantified. There are ongoing and even exacerbated challenges to build intelligent systems, modeling multifaceted phenomena, and deliver efficient models that help users describe and understand systems and support processes of decision-making. We have to become fully cognizant that processing and modeling has to be realized with the use of entities endowed with well-defined semantics, namely information granules. Human do not perceive reality and reason in terms of numbers but rather utilize more abstract constructs (information granules), which are helpful in setting up a certain cognitive perspective and ignore irrelevant details when dealing with the complexity of the systems.

Dutta, Palash

2015 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2015.03.002

AbstractDempster–Shafer theory of evidence is one of the important tools for decision making under uncertainty. It is more useful in situations when cost of technical difficulties is involved or uniqueness of the situation under study makes it difficult/impossible to cover enough observations to quantify the models with real data. Consequently, experts provide opinions in terms of basic probability assignment for focal elements. Usually, it is seen that experts provide basic probability assignment for interval (or crisp) focal elements. However, due to presence of uncertainty focal elements can sometimes be treated as normal/generalized triangular fuzzy number (TFN in short) instead of intervals or crisp sets. TFN encodes only most likely value (mode) and the spread. This paper presents an attempt to combine Dempster–Shafer structures (DSS in short) with generalized/normal fuzzy focal elements using possibilistic sampling technique. To this end, human health risk assessment is carried out under such setting.

Barbhuiya, S.R.

2015 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2015.03.003

AbstractIn this paper, we introduce the concept of -intuitionistic fuzzy ideals of -algebra and investigate some of their basic properties.

Rajkhowa, Kukil Kalpa; Saikia, Helen K.

2015 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2015.03.004

AbstractIn this paper, we discuss the graphical aspects of fuzzy algebra. Let be an with zero element and be collection of all fuzzy submodules of . The intersection graph of is an undirected graph with vertex set as and two vertices and are adjacent if and only if , where is the characteristic function on . We find the girth of and also study some properties of center of .

Saeidifar, A.

2015 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2015.03.005

AbstractThe aim of this paper is to introduce the weighted possibilistic characteristic functions (PCF) of fuzzy numbers and find the close form expressions for triangular, trapezoidal and some other fuzzy numbers. A. Paseka et al. (2011) introduced possibilistic moment generating functions (MGF) of fuzzy numbers. In a general case, the MGF may not be existing, but the PCF has a principle advantage that always exists. Besides, applications involve derivation of higher order possibilistic moments of volatility models, skewness, kurtosis, and correlations, etc. of fuzzy numbers.

Nilavu, D.; Sivakumar, R.

2015 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2015.03.006

AbstractNowadays semantic web languages play a vital role in representing ontologies. In order to deal with uncertainty in the semantic web languages, we need a concrete procedure to represent such information. We may tackle this problem by extending the current semantic web languages with uncertainty. In this article, we extend the current standard language OWL2 (version 2 of the Web Ontology Language), to deal with uncertainty features and also propose an appropriate methodology to represent type-2 fuzzy rough ontologies by the aid of OWL2 annotation properties. We also provide a plug-in, used to edit type-2 fuzzy rough ontologies using OWL2 annotation properties and parsers that translate the type-2 fuzzy rough ontologies into the languages supported by current description logic (DL) reasoners. Moreover, we conduct a large user group study to prove the effectiveness of the proposed work.

Soni, Hardik N.; Joshi, Manisha

2015 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2015.03.007

AbstractIn this paper, an attempt has been made to develop a periodic review inventory model by considering lead-time and the backorder rate as control variables in fuzzy stochastic environment. Without loss of generality, we have assumed that all the observed values of the fuzzy random variable, representing the demand as triangular fuzzy numbers. The variance of fuzzy random demand is taken into consideration to give due attention to every fuzzy observations. The protection interval demand has also been assumed to be fuzzy stochastic. The expected shortages are calculated by using credibility criterion. For the proposed model, we provide a solution procedure incorporating numerical technique viz. Scan and zoom method to determine an optimal policy. A numerical example is taken up to illustrate the solution procedure and sensitivity analysis of the optimal solution with respect to the key parameters of the system is carried out.

Hu, Ren-Jie; Li, Qing; Zhang, Guang-Yu; Ma, Wen-Cong

2015 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2015.03.008

AbstractThe centrality of actors has been a key issue in undirected fuzzy social network (UFSN) analysis. For undirected fuzzy social networks (UFSNs) where edges are just a present or absent undirected fuzzy relation with no more information attached. There has been a growing need to design centrality measures for directed fuzzy social networks (DFSNs), because DFSNs where edges are attached with directed fuzzy relation would contain rich information. In this paper, we propose some new centrality measure called fuzzy in-degree centrality, fuzzy out-degree centrality, fuzzy in-closeness centrality and fuzzy out-closeness centrality which are applicable to the DFSNs. It unveils more structural information about directed fuzzy relation and connectivity of DFSNs. Furthermore, by investigating the validness and robustness of this new centrality measure by illustrating this method to some cases and we obtain reliable results, which provide strong evidences of the new measures’ utility.