To study the problem of knowledge translation in fuzzy approximation spaces, the concept of rough communication of crisp set in fuzzy approximation spaces is proposed. In a rough communication of crisp set in fuzzy approximation spaces, the problem of uncertainty exists, for each agent has a different language and cannot provide precise communication to each other. By means of some concepts, such as CF rough communication cut, which is a bridge between fuzzy concept and crisp concept, cut analysis of CF rough communication is made, and the relation theorem between CF rough communication and rough communication of crisp concept is obtained. Finally, in order to give an intuitive analysis of the relation between CF rough communication and rough communication of crisp concept, an example is given.
Based on the definition of class shortest path in weighted rough graph, class shortest path algorithm in weighted rough graph is presented, which extends classical shortest path algorithm. The application in relationship mining shows effectiveness of it.
In rough communication, because each agent has a different language and cannot provide precise communication to each other, the concept translated among multi-agents will loss some information and this results in a less or rougher concept. With different translation sequences, the problem of information loss is varied. To get the translation sequence, in which the jth agent taking part in rough communication gets maximum information, a simulated annealing algorithm is used. Analysis and simulation of this algorithm demonstrate its effectiveness.
