Session Program


  • 12 July 2017
  • 02:30PM - 04:30PM
  • Room: Catalana
  • Chairs: Sarah Greenfield,Francisco Chiclana and Scott Dick

Complex Fuzzy Sets and Logic

Abstract - In this paper, we propose the complex neutrosophic soft set model, which is a hybrid of complex fuzzy sets, neutrosophic sets and soft sets. The basic set theoretic operations and some concepts related to the structure of this model are introduced, and illustrated. An example related to a decision making problem involving uncertain and subjective information is presented, to demonstrate the utility of this model.
Abstract - Cross-border E-commerce has grown exponentially in the past decade. To gain global competitivity in product-convergent markets, China's over 200 thousands cross- border E-commerce businesses have focused more on the service and cost of supply chain downstream. Therefore, selecting appropriate cost control strategy has marked impact on them. In this study, we evaluated three strategic cost control measures according to 10 evaluation criteria by using a complex fuzzy set based model, named C-COPRAS. The C-COPRAS model is an extension of the COmplex PRoportion ASessment (COPRAS) method. This model uses complex fuzzy set to tackle uncertainty and temporal features in given evaluation context. We then apply this model to a case study of helping a Chinese E-commerce business to select strategic cost control measure on supply chain downstream.
Abstract - This paper studies the set operations on maxitive belief structures, which introduced by Yager and Alajlan as a framework for modeling imprecise possibility distributions. Unlike Dempster-Shafer structures, we show that different maxitive belief structures can induce the same upper and lower possibilities. Then the operations on maxitive belief structures might not be the operations on their induced upper and lower possibilities. We call those operations on maxitive belief structures which are also the operations on their induced upper and lower possibilities the nice operations. We introduce the set operations on maxitive belief structures, including weighted sum, intersection, union, complement, projection, cylindrical extension and Cartesian product operations. We show that the weighted sum, union, projection and cylindrical extension are nice operations, and the intersection, complement and Cartesian product operations are not nice.
Abstract - Multiples studies have shown that time series forecasting algorithms based on complex fuzzy sets and logic can be both very accurate, and simultaneously very compact. There have as yet, however, been no corresponding studies of time series classification, even though it seems reasonable that similar advantages would be obtained. We propose an inductive learning architecture for time series classification based on complex fuzzy sets and logic. We evaluate this new architecture on a condition monitoring problem: detecting the onset of illness in feedlot cattle via animal-mounted sensors. We find that our new system is at least as accurate as existing approaches.
Abstract - Attribute reduction is an important issue in different frameworks. Formal concept analysis (FCA) and object-oriented concept lattices (which is a generalization of rough sets) have been related in different papers. This contribution studies the attribute reduction in object-oriented concept lattices from the one recently given in FCA. As a consequence, we have proven that the study of the classification of the attributes in absolutely necessary, relatively necessary and unnecessary attributes is equivalent in both frameworks. An illustrative example has also been introduced.
Abstract - Bipolar fuzzy relation equations are given from the fuzzy relation equations introduced by Sanchez in the 1980s considering a negation operator in the equations. Numerous applications require variables that show a bipolar character such as decision making and revenue management, hence the importance of studying bipolar fuzzy relation equations. According to the literature, bipolar max-min equations have already been studied and a characterization of their solutions, by means of a finite set of maximal and minimal solution pairs, has been provided. This paper will present a first study on bipolar max-product fuzzy relation equations with one equation containing different variables, which includes different interesting properties in order to guarantee both their solvability and the existence of the greatest (least) solution or maximal (minimal) solutions. Moreover, a characterization of the solvability of a particular system of two bipolar max-product fuzzy relation equations is given.