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Back-propagation (BP) neural network models were developed to accurately predict the ignition temperature and activation energy of 16 typical Chinese coals and 48 of their blends. Pearson correlation analysis showed that ignition temperature and activation energy were most relevant to the moisture, volatile matter, fixed carbon, calorific value and oxygen of coals. Accordingly, three-layer BP neural...
Back-propagation (BP) neural network models were developed to accurately predict the maximum burning rate and fixed carbon burnout efficiency of 16 typical Chinese coals and 48 of their blends. Early stopping method was used to prevent the BP neural network from over-fitting. The generalisation performance and prediction accuracy of the neural network thus became significantly improved. Pearson correlation...
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