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An adaptive neuro–fuzzy inference model for prediction of coal char conversion in CO2 gasification

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Today, in industry, the gasification of coal as an important energy source is an interesting perspective. In this study, the application of adaptive neuro–fuzzy inference system (ANFIS) technique for estimation of char conversion in CO2 gasification is investigated. The main variables affecting char conversion are particle size, reaction time, and reaction temperature, which are chosen as input variables of the proposed model. Experimental data which are gathered from the literature are applied for training, testing, and validation of developed ANFIS model. The results reveal the exact estimation of char conversions with the corresponding experimental values with the regression coefficients (R 2) greater than 0.99.
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Keywords: ANFIS algorithm; coal char; conversion; gasification; modeling

Document Type: Research Article

Affiliations: Petroleum Refining Technology Development Division, Research Institute of Petroleum Industry (RIPI), Tehran, Iran

Publication date: January 2, 2019

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