
## Knowledge Discovery Of Hydrocyclone'S Circuit Based On Sonfis &Sorst

H. O. Ghaffari, M. Ejtemaei, M. Irannajad Amirkabir University of Technology, Faculty of Mining, Metallurgical and Petroleum Engineering, Tehran, Iran 

## Abstract:

This study describes application of some approximate reasoning methods to analysis of hydrocyclone performance. In this manner, using a combining of Self Organizing Map (SOM), Neuro-Fuzzy Inference System (NFIS)-SONFIS- and Rough Set Theory (RST)-SORST-crisp and fuzzy granules are obtained. Balancing of crisp granules and non-crisp granules can be implemented in close-open iteration. Using different criteria and based on granulation level balance point 
(interval) or a pseudo-balance point is estimated. Validation of the proposed methods, on the data set of the hydrocyclone is rendered. Keywords: Information granulation theory, SOM, NFIS, RST, hydrocyclone 1. INTRODUCTION: In the design of mineral processing circuit, one of the most important issues is the selection of hydrocyclone in different parts of the circuit. However, prediction of hydrocyclone performance using direct or indirect modeling has its own difficulties. In recent years application of intelligent methods, in data analysis 
(knowledge discovery) or control process in mineral engineering has been extended (Carvalho and Durao, 2002; Vieira et al., 2005). 

The most main distinguished facets of the soft granules are: set theory, interval analysis, fuzzy set, rough set. Each of these theories considers part of uncertainty of information (data, words, pictures...).Due to association of uncertainty and vagueness with the monitored data set, particularly, resulted from the laboratory or industrial tests, accounting relevant approaches such probability, Fuzzy Set Theory 
(FST) and Rough Set Theory (RST) to knowledge acquisition, extraction of rules and prediction of unknown cases, more than the past have been distinguished. 

The RST introduced by Pawlak has often proved to be an excellent mathematical tool for the analysis of a vague description of object (Pawlak, 1991) the adjective vague, referring to the quality of information, means inconsistency, or ambiguity which follows from information granulation. The rough set philosophy is based on the assumption that with every object of the universe, is associated a certain amount of information, expressed by means of some attributes used for 