危化品气体泄漏事故严重威胁公共安全与环境，精准定位泄漏源强度和位置至关重要。针对传统泄漏源反算方法存在耗时长，精度不足等问题，提出了一种基于多策略改进的哈里斯鹰优化算法，用于气体泄漏扩散事故的高效反演。首先，通过Logistic-Tent复合混沌映射初始化鹰群的位置，以提高种群多样性和全局搜索能力；其次，引入精英等级策略对种群进行科学划分，以此强化算法的局部搜索能力和寻优精确度；最后，采用对数函数非线性衰减策略灵活调整逃逸能量，确保算法性能实现平滑过渡与优化。实验结果表明，改进后的哈里斯鹰优化算法在优化效率和反演精度方面均有显著提升，即便在复杂地形条件下，也能将泄漏源位置和强度的相对误差精确控制在1.00%以内。该方法极大地增强了泄漏源定位的精准度和响应速度，为事故应急辅助决策提供了坚实可靠的解决方案。

Hazardous chemical gas leakage accidents pose significant threats to public safety and the environment, and how to accurately locate the leakage source strength and location is particularly important. Aiming at the defects of traditional leak source inversion methods such as long duration and low accuracy, this study proposes an efficient inversion method based on a multi-strategy improved Harris Hawk optimization algorithm. Firstly, the position of the Harris Hawk swarm is initialized using Logistic-Tent composite chaotic mapping to improve population diversity and global search capability. Secondly, an elite level strategy is employed to scientifically divide the population, thereby enhancing the local search ability and optimization accuracy of the algorithm. Finally, a logarithmic function is adopted to flexibly adjust the escape energy and achieve a smooth transition in algorithm performance. The results show that the improved Harris Hawk optimization algorithm has achieved significant improvements in both optimization efficiency and inversion accuracy. Even under complex terrain conditions, it can accurately control the relative error of the leakage source intensity and location within a maximum of 1.00%. This method greatly improves the accuracy and response speed of leakage source localization, providing a reliable solution for emergency decision-making in accidents.