Journal
ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS
Volume 39, Issue 16, Pages 1778-1784Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/15567036.2017.1370513
Keywords
Combustion; higher heating value; Levenberg Marquardt; RBFANN; solid waste
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Waste combustion is considered as a promising method of energy production due to their proper higher heating value (HHV) to be used as fuels. In this study, HHV values are estimated using a radial basis function artificial neural network (RBFANN) combined with Levenberg Marquardt algorithm as the optimization method. HHV values are predicted using mass percentages of water, carbon, oxygen, hydrogen, nitrogen, sulfur, and ash in the solid waste. The proposed RBFANN is then compared with other available correlations, revealing a great accuracy in prediction of HHV values with mean squared error (MSE) and R-2 values of 0.248 and 0.997, respectively. Therefore, the proposed RBFANN is considered a reliable predictive tool to estimate the wastes' HHV values.
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