Thermal power generation has been widely used in many development fields, and its application in power plant boilers has received the attention of many research teams in recent years. Artificial intelligence algorithms have been applied to the prediction and optimisation of complex variables in various industrial sites, and many results have been achieved with promising development, of which the particle swarm algorithm is a common intelligent optimisation algorithm. Therefore, this paper uses the particle swarm optimisation algorithm to establish a support vector machine prediction model to analyse and predict the operating state of a boiler when it is in online operation. This paper uses the support vector machine to search for the global optimal solution to obtain the optimal output variables in the boiler combustion process. These output variables can include boiler efficiency, NOx emission concentration, etc. Through the optimisation of these target variables, the boiler combustion in power plants can achieve the goal of energy saving and emission reduction.

Guang Guo. Combining Artificial Intelligence Algorithm to Study the Application of Power Plant Boiler in Thermal Power. Kinetic Mechanical Engineering (2022), Vol. 3, Issue 3: 46-53. https://doi.org/10.38007/KME.2022.030306.

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