Combined Grey Wolf Optimizer Algorithm and Corrected Gaussian Diffusion Model in Source Term Estimation

It is extremely critical for an emergency response to quickly and accurately use source term estimation (STE) in the event of hazardous gas leakage. To determine appropriate algorithm, four swarm intelligence optimization (SIO) algorithms including Gray Wolf optimizer (GWO), particle (PSO), genetic algorithm (GA) ant colony (ACO) are selected be applied STE. After calculation, all can obtain leak parameters. Among them, GWO GA have similar computational efficiency, while ACO computationally inefficient. Compared with GWO, PSO, requires larger population more iterations ensure accuracy Most notably, convergence factor self-adaptive, which favor obtaining accurate results lower iterations. On this basis, combination a modified Gaussian diffusion model surface correction used estimate emission work. The calculation demonstrate that corrected plume improve STE, promising application warning safety monitoring.