Emergent Model Based On Hybrid Rough Sets Systems

The development of many knowledge discovery methods provided us with a good foundation for building hybrid systems based on rough set theory for knowledge discovery in a database. The need for more effective methods of generating and maintaining global nonfunctional properties suggests an approach analogous to those of natural processes in generating emergent properties. An emergent model allows the constraints of the task to be represented more naturally and permits only pertinent task-specific knowledge to emerge in the course of solving the problem. This paper describes some basics of emergent phenomena and its implementation in the hybrid system of rough sets combined with other methods. Further, demonstrations and guidelines are presented on how to exploit emergent intelligence and extend the problem-solving capabilities of these hybrid systems.