Fuzzy Information and Engineering

Kar, S.; Shikari, A.

2016 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2016.03.001

AbstractIn this paper, we introduce the notion of soft ternary semiring by using the concept of soft set theory. Besides, we characterize the notions of regularity and intra-regularity in soft ternary semiring by using different soft (left, lateral, right, quasi, bi) ideals of soft ternary semirings.

Mosleh, M.; Otadi, M.

2016 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2016.03.002

AbstractIn this paper, we prove some results concerning the existence of solution of a class of nonlinear fuzzy Fredholm integro-differential equations. Also an iterative approach is proposed to obtain approximate solution of a class of nonlinear fuzzy Fredholm integro-differential equation of the second kind. A numerical example is presented to illustrate the proposed method.

Mathew, Jill K.; Mathew, Sunil

2016 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2016.03.003

AbstractIn a fuzzy graph, the edges are mainly classified into , and . In this paper, some sequences in fuzzy graphs are introduced, whose concepts are based on the classification of edges. Besides, characterizations for blocks in fuzzy graphs and fuzzy trees are obtained. It is shown that sequence of a fuzzy tree is a zero sequence and sequence of a block is a binary sequence.

Das, Satyajit; Guha, Debashree

2016 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2016.03.004

AbstractThe objective of this paper is to introduce a novel method to compare trapezoidal intuitionistic fuzzy numbers (TrIFNs). Till now little research has been done regarding the ranking of TrIFNs. This paper first reviews the existing ranking methods and shows their drawbacks by using several examples. In order to overcome the drawbacks of the existing methods, a new ranking method of TrIFNs is developed by utilizing the concept of centroid point. For this purpose, centroid point for TrIFN is also defined. The rationality validation of the proposed centroid formulae is proved. Further, the ranking method is applied to a multi-criteria decision making (MCDM) problem in which the ratings of the alternatives on criteria are expressed with TrIFNs. Finally, the effectiveness and applicability of the proposed ranking method are illustrated with an aerospace research organization center selection example. This article has also justified the proposed approach by analyzing a comparative study.

Tom, Mini; Sunitha, M. S.

2016 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2015.07.001

AbstractIn this paper, the concepts of boundary nodes and interior ones are introduced in a fuzzy graph based on sum distance with relationship among boundary nodes, interior nodes, fuzzy cutnodes and complete nodes. It is observed that fuzzy cutnodes can be boundary nodes and there are nodes in , neither boundary nodes nor interior ones. It is verified that a complete node need not be a boundary one and a node which is a boundary one of all other nodes need not be complete. In fuzzy trees, it is observed that fuzzy end nodes need not be boundary ones and vice versa. It is verified that in a complete fuzzy graph there exist at most one node which is not a boundary one. Also boundary nodes of a self centered fuzzy cycle are identified together with interior nodes of a complete fuzzy graph.

Thakur, Gour Sundar Mitra; Bhattacharyya, Rupak; Mondal, Seema Sarkar

2016 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2016.03.005

AbstractInflation can be attributed to both microeconomic and macroeconomic factors which influence the stability of the economy of any nation. With the raising of recession at the end of the year 2008, world communities started paying much contemplation on inflation and put enormous hard work to predict it accurately. Prediction of inflation is not a simple task. Moreover, the behavior of inflation is so complex and uncertain that both economists and statisticians have been striving to model and forecast inflation in an accurate way. As a result, many researchers have proposed inflation forecasting models based on different methods; however the accuracy is always being a major constraint. In this paper, we have analyzed the historical monthly economic data of India between January 2000 and December 2012 and constructed an inflation forecasting model based on feed forward back propagation neural network. Initially some critical factors that can considerably influence the inflation of India have been identified, then an efficient artificial neural network (ANN) model has been proposed to forecast the inflation. Accuracy of the model is proved to be satisfactory when compared with the forecasting of some well-known agencies.

Bessissa, Lakhdar; Boukezzi, Larbi; Mahi, Djillali

2016 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2016.03.006

AbstractIn this work, we have used the fuzzy logic approach to predict mechanical properties (hot set test) of cross-linked polyethylene (XLPE) used as insulation in high voltage cables. The studied property presents non linear variations according to the aging time under high temperatures. So it is very difficult to find a theoretical or experimental model of the properties evolution under thermal aging. For that reason, several factors have been considered such as aging time and applied temperature. The obtained results are very encouraging and pointed out that the fuzzy logic is a powerful tool to predict the insulation proprieties. In other words, the obtained results are in good accordance with the experimental results with an acceptable error margin.

Bhawsar, Y.; Thakur, G.S.

2016 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2016.03.007

AbstractLink prediction in social networks represents a significant task in understanding the behavior and actions of users. There are various methods to it and some of them are Jaccard’s Coefficient, Common Neighbor, and Sorenson etc. These methods predict the link correctly but sacrifice with efficiency. The reasons behind this are discussed in this paper with two new methods of link prediction to improve the efficiency. These methods are based on fuzzy soft set and Markov model. We analyze that the proposed work predicts more accurately links as compared to existing methods.