Models Predicting Calorific Value of Straw from the Ash Content

The use of straw for energy production has become increasingly popular in China today. To develop fast and cheap analysis, the calorific values of 222 straw samples from rural China were correlated with their ash content. Linear regression equation, nonlinear fitting equation, and artificial neural network models were developed in this study to investigate the feasibility of predicting calorific value from ash content. All three methods resulted in good models; when evaluated on independent validation, root mean square error presented were 284 J/g, 255 J/g, and 241 J/g, respectively. It was therefore concluded that good predictions for calorific value can be achieved by models based on ash content.