Sharif Digital Repository

One of the important parameters in development of bioenergy industry and economical investigation of fuels is higher heating value (HHV) of biomass in the present study; multi-layer perceptron (MLP) artificial neural network was applied to predict HHV of biomass in terms of volatile matters (VMs), fixed carbon (FC), and ash content (ASH). The purposed algorithm was trained and tested by utilizing 350 experimental data points which extracted from literature. Based on results, the MLP-ANN has great ability to estimate HHV for biomass. This method can be developed as a user-friendly software for prediction of HHV of the fuel in terms of proximate analysis. The predicting software can be wide... 

One of the important parameters in economic study of energy sources and bioenergy is higher heating value (HHV). In this investigation, adaptive neuro fuzzy inference system (ANFIS) was applied as a novel method to predict HHV of biomass in terms of fixed carbon (FC), ash content (ASH), and volatile matters (VMs). Due to the fact that experimental investigations are time- and cost-consuming, this investigation was selected purely computational and a total number of 350 experimental data were extracted from literature for different steps of modeling. The proposed algorithm was evaluated by statistical indexes such as coefficient of determination (R2), root mean squared error (RMSE), and...