Based on the fact that the power plant carbon content in fly ash is hard to predict effectively, a nesting-intelligent-integrated prediction method was proposed from improving the prediction accuracy and adaptive ability. Firstly, the variable-learning-rate-based back propagation neural network and principal element analysis method were utilized to reduce the dimension of the input variables. Secondly, in order to improve the adaptive ability of the prediction model, the online support vector machine method was carried on to predict the carbon content in fly ash based on the above analysis res...
