Fuzzy Information and Engineering

Hayat, Khizar; Mahmood, Tahir; Cao, Bing-Yuan

2017 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2017.03.001

AbstractIn this work, we present notions of bipolar anti fuzzy -ideals and bipolar anti fuzzy interior -ideals in hemi-rings. Investigating some of their properties, we characterize hemi-rings by means of positive anti -cut and negative anti -cut. Meanwhile, some results of homomorphisms, anti images and anti pre-images are given to show the rationality of the definitions introduced in the present paper. Also, we define an equivalence relation on bipolar anti fuzzy -ideals. In particular, we investigate translations, extensions and multiplications of bipolar anti fuzzy -ideals. Finally, we present characterizations of h-hemi-regular and h-semi-simple hemi-rings in terms of bipolar anti fuzzy -ideals.

Mandal, Prasenjit; Ranadive, A.S.

2017 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2017.03.002

AbstractThis paper proposes similarity of L-fuzzy relations based on L-topologies induced by L-fuzzy rough approximation operators. First, the notion L-fuzzy rough set is generalized and the relationship between generalized L-fuzzy rough sets and L-topologies on an arbitrary universe is investigated. It shows that Alexandrov L-topologies can be induced by L-fuzzy relations without any preconditions. Second, the concept of similarity of L-fuzzy relations is introduced and variations of an L-fuzzy relation are investigated. Third, algebraic structures on similarity of L-fuzzy relations are obtained. Finally, we prove that the subset of the transitive L-fuzzy relations similar to a fixed L-fuzzy relation is a complete distributive lattice.

Gümüş, S.; Bali, O.¨

2017 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2017.03.003

AbstractThe idea of combine aggregation and intuitionistic fuzzy information plays essential role in multi criteria decision making (MCDM) process. However, this new branch has attracted researchers that study in different fields recently. In this paper, we study MCDM problems with intuitionistic fuzzy environment. Firstly, we introduce some operations related with Einstein t-norm and t-conorm such as, Einstein sum, product and exponentiation. After that, we define dynamic intuitionistic fuzzy Einstein averaging (DIFWA) operator and dynamic intuitionistic fuzzy Einstein geometric averaging (DIFWG) operator. Their notable property is that collect and aggregate values in different period based on Einstein operations in intuitionistic fuzzy set (IFS)s. In addition, we compare the defined operators with the existing intuitionistic fuzzy dynamic operators and get the corresponding relations. We establish two methods using with DIFWA and DIFWG to solve MCDM problems with intuitionistic fuzzy tools. Finally, an illustrated example is presented to show the applicability of the introduced methods.

Dutta, Palash; Limboo, Bulendra

2017 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2017.03.004

AbstractA soft set theory is a new general mathematical tool to dealing with imprecision. The theory differs from traditional mathematical tools to dealing with uncertainties in which many mathematical theories failed. In this paper, we proposed the concept of Bell shaped fuzzy soft set and its application in medical diagnosis using arithmetic operations of discrete- Gaussian fuzzy number, triangular-Cauchy fuzzy number and Gaussian-Cauchy fuzzy number. As an integral part of this paper, we discuss the parametric form of Gaussian membership function is discussed with some important properties.

Gulistan, Muhammad; Khan, Madad; Yaqoob, Naveed; Shahzad, Muhammad

2017 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2017.03.005

AbstractIn this article we characterize the regular LA-semihypergroups in terms of -cubic (left, right, two sided, bi, generalized bi, interior, quasi)-hyperideals of LA-semihypergroups. Meanwhile, some illustrative examples are given to show the rationality of the definitions popularized in the present paper.

Mukherjee, Sathi

2017 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2017.03.006

AbstractThe unrestrained expansion in urbanization and increasing development of new means of transports result in major urban land use and transportation system which is socially, economically and environmentally unsustainable. Hence the major challenge for the decision makers regarding the transportation policies is to choose the alternative fuel operated vehicles resulting in a sustainable transportation system. In real life situations, it is difficult to get exact data, so to express the uncertain data, intuitionistic fuzzy data has been considered. The problem is to select the best fuel technology for land transportation subject to multiple criterions resulting in a sustainable transportation system in an uncertain environment. Here, the similarity measures of Intuitionistic fuzzy sets (IFSs) are applied for developing a methodology for identifying the best option. The weights of the attributes may be known or partially known or unknown. The unknown weights are determined by normalizing the average score functions of the intuitionistic fuzzy data for the criterion. Algorithms are given for handling different situations and numerical examples illustrate the varied cases.