In this paper, we further investigate the constructions of fuzzy connectives on a complete lattice. We firstly illustrate the concepts of left (right) semi-uninorms and implications satisfying the order property by means of some examples. Then we give out the formulas for calculating the upper and lower approximation implications, which satisfy the order property, of a binary operation.

Many diierent fuzzy implication operators have been proposed; most of them t into one of the two classes: implication operations that are based on an explicit representation of implication A ! B in terms of &, _, and : (e.g., S-implications that are based on the formula B _ :A), and R-implications that are based on an implicit representation of implication A ! B as the weakest C for which C&B i...

In this paper, the authors propose a new hard clustering method to provide objective knowledge on field of fuzzy queuing system. In this method, locally linear controllers are extracted and translated into the first-order Takagi-Sugeno rule base fuzzy model. In this extraction process, the region of fuzzy subspaces of available inputs corresponding to different implications is used to obtain th...

We have proposed a method to identify objects in database schema using association degree with other objects. We have also used identifying attribute of associations in graph to specify a unique path to resolve ambiguity of Fuzzy Object Functional Dependencies. Recently Fuzzy Concepts were used in Object Oriented Data Models. The Object Identifier allows distinguishing between similar objects. ...

We introduce fuzziness to conceptual knowledge processing by using linguistic variables instead of a two-valued representation. The attribute/object table for conceptual lattices holds fuzzy membership values rather than TRUE/FALSE entries and can be mapped into a graph of dependencies. From this graph implications can be extracted together with the method to compute truth values for the inferi...

Fuzzy associative memories belong to the class of fuzzy neural networks that employ fuzzy operators such as fuzzy conjunctions, disjunctions, and implications in order to store associations of fuzzy patterns. Fuzzy associative memories are generally used to implement fuzzy rule-based systems. Applications of FAMs include backing up a truck and trailer, target tracking, human-machine interfaces,...

The practice, common in fuzzy expert systems, to map linguistic data into fuzzy sets has some important reverse implications: given membership functions that represent different terms of a linguistic variable in one natural language , we can set out to search which of them best matches a given term in another language , on the basis of similarity assessments between individual terms. In other w...

This paper considers a single-period product inventory control in a distributed supply chain, which is composed of one manufacturer and one retailer and operates in the environment of uncertain market demand. A Stackelberg model with fuzzy demand is first developed, with using a L–R fuzzy number with a general membership function to depict the fuzzy market demand, and through adopting the weigh...

The paper presents generalizations of results on so-called Horn logic, well-known in universal algebra, to the setting of fuzzy logic. The theories we consider consist of formulas which are implications between identities (equations) with premises weighted by truth degrees. We adopt Pavelka style: theories are fuzzy sets of formulas and we consider degrees of provability of formulas from theori...

In this paper we introduce a new fuzzy evaluation function for examination timetabling. We describe how we employed fuzzy reasoning to evaluate the quality of a constructed timetable by considering two criteria, the average penalty per student and the highest penalty imposed on any of the students. A fuzzy system was created based on a series of easy to understand rules to combine the two crite...