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## 5. Conclusion

This paper has presented a re-granulation method for knowledge discovery, with emphasis on the crisp-sub fuzzy granules extraction. This approach has been applied to aid prediction of hydrocyclone performance and extraction of simple rules, which are agents to control of the split size. The main idea, behind the proposed methodologies, is based on the complexity of information and construction of humanity world cognition by using, as most as, simple rules (in overall structure and number).The competitive between close and open worlds, in a parallel road of the mentioned features, is the additional situation to balancing of the granules and to gain a stable answer. A collected of granules space, associated with the algorithm's variables, can be supposed as an off-line training of the genetic algorithm, which may find best structure and parameters , in complementary vein on the employed method. The results proved the applicability of this method in reducing of data set and elicitation of best simple rules, so that, had a relative good answer on the test data. Authors are developing such algorithms under rough set theory, heuristic optimization methods, balancing and collaborative approaches (owladeghaffari&Babaei,2008) . 