Abstract
In order to meet the requirement of high efficiency and low emission in boiler operations, a hybrid model is established based on experimental data and combined with BP neural network. This model uses the adjustable operation parameters of boiler as inputs and chooses NOx emission and boiler efficiency as outputs to achieve the prediction of NOx emission and thermal efficiency. And it optimizes the combustion process by using genetic algorithm. The results show that it is an applicable and effective numerical optimization method.
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