2. 吉林大学地质资源立体探测虚拟仿真实验教学中心，长春130026

陷入局部极值等问题，笔者提出一种基于混沌搜索和动态步长相结合的萤火虫算法( CAFA) 。在搜

索初期，CAFA 算法使用具有随机性、有界性和遍历性的混沌序列设置萤火虫种群初始位置; 利用一

种新型双曲线递减动态步长代替传统固定步长。经过上述改进提高了种群分布的均匀性、求解精度、

收敛速度以及避免迭代后期出现反复振荡现象。将CAFA 算法应用于地震资料波阻抗反演，利用理论

模型论证算法可行性、有效性和抗噪性。实验结果表明CAFA 算法具有较好反演效果。

2. Geological Ｒesources Stereo Exploration Virtual Simulation Experimental Teaching Center，Jilin University，

Changchun 130026，China

search，the CAFA algorithm uses a random，bounded and ergodic chaotic sequence to set the initial position of the firefly population; a new type of hyperbolic decreasing dynamic step size is used to replace the traditional fixed step

size． These improvements enhance the uniformity of population distribution，solution accuracy，and convergence speed，and avoid the repeated oscillation phenomenon occurred at later stages． The theoretical models demonstrate

the feasibility，effectiveness and noise immunity of the CAFA algorithm，when it is applied to seismic wave impedance inversion． Experimental results show that the CAFA inversion algorithm has a good inversion effect．