Analysis of hydrocyclone performance based on information granulation theory

TL;DR

This paper introduces a novel method combining Self Organizing Map and Neuro-Fuzzy Inference System, called SONFIS, to analyze hydrocyclone performance using information granulation theory, ensuring stability through specific criteria.

Contribution

The paper presents a new hybrid approach, SONFIS, for hydrocyclone analysis that balances crisp and fuzzy granules with stability guarantees.

Findings

Method effectively models hydrocyclone performance.

Algorithm maintains stability via rule simplicity and error thresholds.

Validation confirms the approach's applicability.

Abstract

This paper describes application of information granulation theory, on the analysis of hydrocyclone perforamance. In this manner, using a combining of Self Organizing Map (SOM) and Neuro-Fuzzy Inference System (NFIS), crisp and fuzzy granules are obtained(briefly called SONFIS). Balancing of crisp granules and sub fuzzy granules, within non fuzzy information (initial granulation), is rendered in an open-close iteration. Using two criteria, "simplicity of rules "and "adaptive threoshold error level", stability of algorithm is guaranteed. Validation of the proposed method, on the data set of the hydrocyclone is rendered.