Abstract
ABSTRACTCombustion 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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Energy Sources, Part A: Recovery, Utilization, and Environmental Effects
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
