Real-time prediction method for nitrogen oxide concentration of flue gas system of thermal power plant based on random forest

The invention discloses a thermal power plant flue gas system nitrogen oxide concentration real-time prediction method based on a random forest. The method specifically comprises the following steps: obtaining and preprocessing process data; sorting the importance degrees of the variables and screening the variables; constructing a nitrogen oxide prediction model, and setting model parameters; and carrying out online deployment on the prediction model. According to the method, automatic screening of the key variables is realized based on process data which can be acquired in real time, the nitrogen oxide prediction model with high robustness and high precision is constructed, and the method has relatively good practicability and generalization performance, is beneficial to improving the nitrogen oxide detection efficiency of the flue gas system of the thermal power plant, and provides a basis for the thermal power plant to control nitrogen oxide emission. 本发明公开了一种基于随机森林的火电厂烟气系统氮氧化物浓度实时预测方法，该方法具体包括以下步骤：过程数据的获取