Research on method of orientating sudden pollution source based on ELM and sequential UKF

In this paper, from the problem of the orientation of sudden pollution source which continuously release pollutants in three-dimensional space, while the orientation of the pollution source in the real environment is random and complex under the influence of the internal movement factors of the lake reservoir fluid, the problems are discussed from two aspects. Firstly, the nonlinear least squares estimation is carried out based on the pollution source diffusion model. Then, the sequential idea is combined with the sequential unscented Kalman filter, and the pollution source is precisely orientated by using the sequential unscented Kalman filter. Secondly, under the condition that the pollutant diffusion model is unknown, the diffusion model of pollutants in the unknown diffusion model is trained by ELM to solve the problem of the orientation of sudden pollution sources. The simulation results show that the ELM trains a pollutant concentration diffusion equation, which can effectively avoid the influence of internal movement, wind or other factors, and more in line with the actual environment. After training the concentration diffusion model, it is possible to reduce the complexity of numerical calculation, improve the performance of orientation and improve the robustness of orientating based on the application of the sequential unscented Kalman filter.