小样本机器学习的激光传输效能评估方法  

Evaluation Method of Laser Transmission Efficiency Based on Small Sample Machine Learning

作　　者：冷坤 杨云涛 黄雁华 周璇 武文远 LENG Kun;YANG Yuntao;HUANG Yanhua;ZHOU Xuan;WU Wenyuan(Army Engineering University of PLA,Nanjing 211101,China)

机构地区：[1]陆军工程大学,江苏南京211101

出　　处：《陆军工程大学学报》2024年第3期36-42,共7页Journal of Army Engineering University of PLA

基　　金：江苏省自然科学基金面上项目(BK20211225)。

摘　　要：为解决激光大气传输外场试验数据集中特征量不足的小样本问题,通过多层相位屏算法构建了激光大气传输模型,获取了4000多组仿真数据,与332组近红外激光大气传输外场试验数据组成机器学习训练数据集。将大气参数、传输距离等作为输入项,4种到靶光斑的光场评价因子作为输出项,利用随机森林算法训练光场评价因子预测模型,实现激光大气传输效能评估,并利用202组实测外场数据对模型有效性进行验证。研究结果表明,随机森林算法构建的模型R2系数在0.89以上,可以较好地拟合输入与输出之间的多元回归关系;模型预测结果与真实试验结果的平均相对误差在10%以下,预测精度较高。研究结果可为机器学习算法在激光传输效能评估中的应用提供一定的科学依据,为激光大气传输效能评估提供一定的技术支撑。In order to solve the small sample problem of insufficient feature quantity in the laser atmospheric transmission field test dataset,a laser atmospheric transmission model was constructed by the multi-layer phase screen algorithm,and more than 4000 sets of simulation data were obtained.The simulation data,together with 332 sets of near-infrared laser atmospheric transmission field test data,form the machine learning training data set.With the atmospheric parameters,transmission distance,and other parameters as input items,and four evaluation factors for the target spot light field as output items,the random forest algorithm was used to construct a prediction model of four light field evaluation factors to achieve assessment of laser atmospheric transmission efficiency.The effectiveness of the model was verified using 202 sets of real field data.The research results show that the R2 coefficient of the model constructed by the random forest algorithm is above 0.89,which can better fit the multiple regression relationship between input and output;the average relative error between the predicted value and the experimental value is less than 10%,which indicates that the prediction accuracy of the model is high.The research results can provide certain scientific basis for the application of machine learning algorithms in laser transmission effectiveness evaluation,and provide certain technological support for the evaluation of laser atmospheric transmission effectiveness.

关 键 词：激光大气传输 效能评估 随机森林算法 小样本机器学习 

分 类 号：O432.1[机械工程—光学工程]