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As a basis for denitration of coal-fired power plant, the measurement of nitrogen oxide (NOX) content at the inlet of the Selective Catalytic Reduction (SCR) reactor is critical. In order to solve the problem that the NOX content cannot be accurately measured in real time, a soft sensing model based on regression support vector machine (SVR) is proposed. Firstly, the process of generating NOX at the inlet of SCR reactor is analyzed. Then auxiliary variables are selected by correlation analysis and principal component analysis, and the mathematics model based on support vector machine for regression algorithm is built. Finally, the model is tested by the method of BP artificial neural network. The proposed model lays the foundation for the real-time and accurate measurement of the NOX concentration at the inlet of the SCR reactor.