International Journal of Computer Science and Informatics


Theory of knowledge has a long and rich history. Various aspects of knowledge are widely discussed issues at present, mainly by logicians and artificial intelligence (AI) researchers. It is one of the concepts, used to build intelligence system. Many soft computing tools are available for extraction, acquisition and validation of knowledge. Rough set is one such tool, mainly used for classification and extraction of knowledge. Rough Set Theory was proposed by Pawlak in 1982 as a tool for knowledge Extraction. However, when knowledge extraction is studied, we observed that most of the knowledge is static in nature. For analyzing Knowledge having dynamic in nature, Pawlak’s Rough Set Theory must be reconsidered. Dong Ya Li (et. al.) has already proposed the concept of dynamic Rough Set in 2007. We here, further analyze this concept and try to find out some more properties of it. Dynamic Rough Set (D-rough set) is a common form of Pawlak’s Rough Set as Pawlak’s rough set can be considered as a special case of D-rough set. Drough set is based on concepts, such as elementary transfer coefficient. D-rough set and D-Approximate set can be used for studying and analyzing dynamic knowledge. Further, we study and analyze the properties mentioned by Bussee. Grzymala-Busse has established some properties of approximation of classifications. These results are irreversible by nature. Pawlak has noted that these results of Busse establish that the two concepts, approximation of sets and approximation of families of sets (or classifications) are two different issues and that the equivalence classes of approximate classifications cannot be arbitrary sets. He has further stated that if we have positive example of each category in the approximate classification then we must have also negative examples of each category. In this paper, we have mentioned these aspects of the theorems of Busse and tried to study their properties, when D-rough and D-Approximate set has been incorporated. Lastly, we had provided the physical interpretation of each one of them.



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