Fuzzy Information and Engineering

Xie, Ning-Xin

2016 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2016.06.001

AbstractSoft set theory is a mathematical tool for dealing with uncertain. In this paper, the parameter reduction of soft sets is investigated by means of the attribute reduction in information systems and its algorithm is obtained. Moreover, an example is given by using this algorithm.

Huang, Bing; Li, Hua-Xiong; Feng, Guo-Fu; Zhuang, Yu-Liang

2016 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2016.06.002

AbstractInformation granularity and hierarchical structures in granular computing are the two main aspects for investigating the uncertainty and structure of all types of granular spaces. This study presents a distance-based information granularity for IF and multi-granulation IF granular spaces and use it to construct a novel hierarchical structure on such spaces. First, we propose a distance and a relative distance between two IF granular structures to differentiate them and use these two distances to generalize the axiomatic approach of fuzzy information granularity to the IF context. Second, we construct a hierarchical structure based on the relative distance between two IF granular structures to organize the IF granular space hierarchically. Third, we provide the multi-granulation IF granular space and study its relative-distance based axiomatic approach of IF information granularity. Fourth, we propose a relative-distance-based hierarchical structure on multi-granulation IF granular space.

Da Silva, I.A.; Bedregal, B.; Santiago, R.H.N.

2016 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2016.06.003

AbstractThe linearity contained in the natural order of unit interval plays an important role in many concepts and applications of fuzzy theory. Besides, it is very important in concepts like ordered weighted aggregation operators (OWA) and fuzzy decision making. However, this linearity is not inherited by most of fuzzy logics which extend the standard one. To recover the linearity for such frameworks it is required that its related partial order to be extended give rise to the notion of admissible order. In this paper, we study some admissible orders for the framework of interval-valued intuitionistic fuzzy logic.

Luo, Min-Xia; Cheng, Ze

2016 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2016.06.004

AbstractIn this paper, we focus on the parametric triple I algorithms by the combination of Schweizer–Sklar interval-valued operators and triple I principles for fuzzy reasoning. Firstly, we give the interval-valued triple I solutions based on Schweizer–Sklar interval-valued operators. Then, we investigate the sensitivity of Schweizer–Sklar interval-valued fuzzy connectives. Finally, we study the robustness of the triple I algorithms based on Schweizer–Sklar interval-valued t-norms (). It shows that the quality of interval-valued fuzzy reasoning algorithms depends on the selection of interval-valued fuzzy connectives.

Saha, P.; Choudhury, Binayak S.; Das, Pradyut

2016 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2016.06.005

AbstractCoupled coincidence and fixed point problems have been in the focus of the research interest for last few years. The problem was introduced in fuzzy metric spaces only very recently. In this paper, we work out a weak coupled coincidence point theorem for a compatible pair of mappings in fuzzy metric spaces. As one of the corollaries we have a weak coupled fuzzy contraction mapping theorem. The space is endowed with a partial ordering. We use a combination of analytic and order theoretic concepts in the proof of our main theorem. The result is illustrated with an example.

Zhang, Gang-Qiang

2016 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2016.06.006

AbstractAn approximation space is a key concept in rough set theory, which plays an important role to approximate reasoning about data. An interval-valued fuzzy (IVF, for short) approximation space is an approximation space in the IVF environment. In this paper, IVF rough approximation operators are investigated with topological structures of IVF approximation spaces given.

Kishore, Anjaly; Sunitha, M.S.

2016 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2016.04.001

AbstractFuzzy graph coloring techniques are used to solve many complex real world problems. The chromatic number of complement of fuzzy graph is obtained and compared with the chromatic number of the corresponding fuzzy graph. The chromatic number of the resultant fuzzy graphs is studied, obtained by various operations on fuzzy graphs like union, join and types of products. A solution to routing problem is suggested by using chromaticity of fuzzy graphs.

Gomathi Nayagam, V. Lakshmana; Jeevaraj, S.; Sivaraman, Geetha

2016 Fuzzy Information and Engineering

doi: 10.1016/j.fiae.2016.06.007

AbstractFuzzy number was introduced by Dubois and Prade [10] to handle imprecise numerical quantities. Later it was generalized to intuitionistic fuzzy number by Burillo et al. [5]. Ranking intuitionistic fuzzy numbers plays an important role in decision making and information systems. All over the world many researchers have proposed different score functions for ranking intuitionistic fuzzy numbers but unfortunately every method produces some anti-intuitive results in certain places. A complete ranking on the entire class of fuzzy numbers have been achieved by W. Wang, Z. Wang [22] using upper dense sequence defined in . But a complete ranking on the set of all intuitionistic fuzzy number remains an open problem till today. Complete ranking on the class of intuitionistic fuzzy interval number was done by Geetha et al. [13]. In this paper, total ordering on the entire class of intuitionistic fuzzy number (IFN) using upper lower dense sequence is proposed and compared with existing techniques using illustrative examples. This new total ordering on intuitionistic fuzzy numbers (IFNs) generalizes the total ordering defined in W. Wang, Z. Wang [22] for fuzzy numbers (FNs).