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GA-ANFIS modeling of higher heating value of wastes: Application to fuel upgrading

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Combustion of wastes is a promising source for energy recovery because of having appropriate higher heating value (HHV) in order to use as fuel. The present study was aimed to estimate HHV value using a hybrid adaptive neuro-fuzzy inference system and genetic algorithm called GA-ANFIS. This model can predict HHV as a function of carbon (%C), hydrogen (%H), oxygen (%O), nitrogen (%N), and sulfur (%S) mass percentages. This suggested model has been also compared with other published correlations, and based on obtained results, great accuracy of our model was confirmed. The obtained values of Mean Squared Error (MSE) and R-squared were 0.236 and 0.9983, respectively. Consequently, this model can be very valuable to have accurate prediction of waste HHV value.
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Keywords: ANFIS; GA; combustion; fuel upgrading; higher heating value

Document Type: Research Article

Affiliations: 1: Department of Chemical Engineering, Amirkabir University of Technology, Mahshar Campus, Mahshahr, Iran 2: Department of Civil and Environment Engineering, Amirkabir University of Technology, Tehran, Iran

Publication date: January 2, 2019

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