###### Abstract  
Charged particles have high momentum under high-temperature conditions, which helps to promote their movement towards a dust collector in a magnetic field environment, making it possible to improve the efficiency of the high-temperature wire-plate electrostatic precipitator (ESP) in this environment. A multi-field coupling model was established to numerically simulate PM2.5 dust-removal efficiency in an ESP under different working conditions. Combining the particle swarm optimization (PSO) algorithm with the support vector machine (SVM) model, the PSO-SVM prediction model is presented. Simulated data were used as training data, and PSO-SVM and back-propagation (BP) neural network models were utilized to predict collection efficiency under different working conditions, respectively. The results show that introducing a magnetic field can effectively improve the PM2.5 collection efficiency of wire-plate ESP, and the effect of a magnetic field on the dust-removal efficiency is more obvious at higher temperatures and higher flue gas velocities. When changing the working conditions, the predicted results of the magnetic field effect conform to simulated ones, and the PSO-SVM predicted values have a smaller relative error than those of the BP model, which can better adapt to different working conditions. All of the above conclusions can be utilized as a simple and adequately efficient example of the ESP model for follow-up research. high-temperature ESP; magnetic effects; flue gas velocity; PM2.5 trapping efficiency; PSO-SVM prediction 2023 13 12714 10.3390/appl32312714 10.  
study on the change rule of PM2.5 under different parameters, the effective measures to improve the dust-removal efficiency and reduce the concentration of PM2.5 emissions have become urgent problems in environmental governance research [3]. [PERSON] et al. [4] conducted a bibliometric analysis of the existing publications on PM2.5 exposure over the past three decades and analyzed the current state and historical trends. They found that the number of publications on PM2.5 exposure has been increasing at an accelerating rate. [PERSON] et al. [5] proposed a quantitative modeling and prediction method for sustained rainfall-PM2.5 removal modes on a micro-temporal scale, citing the reasonableness and effectiveness of the proposed method. This work established a magnetic field environment to add the magnetic effect on the basis of ESP to control the tiny particles whose principle is to attach an external magnetic field to the wire-plate ESP. Therefore, the charged PM2.5 particles would generate Lorentz force under the action of the magnetic field and realize the control of the motion trajectory of the charged particles, so as to achieve the purpose of dust collection. [PERSON] et al. [6] created a high-flue-gas condition to capture fine particles, and the experimental results showed that the fine magnetic particles could be successfully caught in a high-gradient magnetic field environment. [PERSON] et al. [7] studied particle dynamics in a magnetic field environment and constructed a trajectory equation for particles in incompressible viscous fluids based on magnetic field force, viscous force, and gravity. [PERSON] et al. [8] simulated the critical path line, indicating the magnetic collection threshold position through the numerical evaluation of particle velocity contours; they found that particle size was one of the most important parameters determining ESP dust collection efficiency under the magnetic effect. [PERSON] [9] proposed a mathematical model of the motion of magnetic abrasive particles (MAPs) and studied the factors affecting the adsorbed instantaneous-effective abrasive particle (IETA) through simulation analysis and experiments, which showed that with the increase in flue gas velocity and the growth rate of IETA, arrest slowed down. [PERSON] et al.