Knowledge Discovery of Hydrocyclone s Circuit Based on SONFIS and SORST
Knowledge Discovery of Hydrocyclone s Circuit Based on SONFIS and SORST
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.
M. Irannajad、M. Ejtemaei、H. O. Ghaffari
水利工程基础科学工程基础科学计算技术、计算机技术
M. Irannajad,M. Ejtemaei,H. O. Ghaffari.Knowledge Discovery of Hydrocyclone s Circuit Based on SONFIS and SORST[EB/OL].(2009-08-01)[2025-07-16].https://arxiv.org/abs/0908.0089.点此复制
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