提出了一种新颖的基于人工神经网络(ANN)和遗传算法(GA)的激光器参数全局优化方法,建立激光器输出功率的人工神经网络模型,来模拟激光器参数对输出功率的综合影响机理,进而以该模型作为目标函数,采用遗传算法对激光器参数进行全局优化。以平凹腔单横模氦氖激光器为例验证了该方法的可行性和有效性。对相同参数的激光器,人工神经网络模型的仿真数据与实验数据的均方根误差为0.0127 mW。应用该方法对其他参数全局优化后激光器预期输出功率比实验室已有的同等尺寸的激光器大,说明了该方法的有效性。 A novel global optimization method of laser parameters based on artificial neural network (ANN) and genetic algorithm (GA) is proposed. An artificial neural network model of laser output power is established to simulate the comprehensive influence mechanism of laser parameters on output power. The model is taken as the objective function, and the genetic algorithm is used to optimize the laser parameters globally. An example of flat cavity single transverse mode He-Ne laser is given to verify the feasibility and effectiveness of this method. For the same parameters of lasers, the root mean square error of simulation data and experimental data of artificial neural network model is 0.0127 mW. After the global optimization of other parameters is applied, the expected output power of the laser is larger than that of the laser of the same size in the laboratory, which shows the effectiveness of the method.