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Improvement of HHV prediction model of biomass based on the ultimate analysis

2021; American Institute of Physics; Volume: 13; Issue: 5 Linguagem: Inglês

10.1063/5.0059376

1941-7012

Se-Ung Kim, Jong Sun Yun, Jong Sim Ri, Kwang Il Hong, Ok Sim Chon, Jin Hyok Ri, Jang Mi Ri,

Forest Biomass Utilization and Management

This paper presents an improved prediction model for the higher heating value (HHV) of biomass based on the ultimate analysis by using the standard least squares method. This study intends for us to predict the HHV of biomass within a wide range of elemental distributions rather than the range of literature in order to create an optimal prediction model. To this end, many experimental data, comprising a wide range of biomass elements, regression models, and neural networks, are used for its comparative validation. As a result, the proposed prediction model, HHV = 2.8799 + 0.2965 * C + 0.4826 * H – 0.0187 * O demonstrates a better HHV prediction performance for biomass in a comparative validation of 250 samples presented in the literature, and the fitness model using a neural network shows a high fitness in the training, validation, and testing for 430 samples.