航空弹药技术保障模拟训练智能评估  

Intelligent Evaluation of Simulation Training for Aerial Ammunition Technical Support

作　　者：徐刚[1] 张磊[1] 田磊[1] Xu Gang;Zhang Lei;Tian Lei(Battle Support Experiment&Simulation Training Center,Air Force Logistics College,Xuzhou 221000,China)

机构地区：[1]空军勤务学院作战保障实验与模拟训练中心,江苏徐州221000

出　　处：《系统仿真学报》2020年第6期1103-1116,共14页Journal of System Simulation

基　　金：空军勤务学院重点青年基金(KY2018F006A)。

摘　　要：量化评估是航空弹药技术保障模拟训练的一个重要环节,为了实现模拟训练自动评估,引入智能评估技术,从中提出一种基于Sigmoid回归的预测模型。在分析成绩指标样本数据线性关系基础上,选择特征指标子集作为预测数学模型的输入,为了避免梯度下降法陷入局部解问题,给出"梯度下降+粒子群"求解算法。经过成绩样本测试,求解算法能够寻找到全局最优解,而且基于Sigmoid模型预测效果没有发生过拟合和欠拟合问题。在实际应用时,可以不需要依赖主观评估成绩,发挥基于计算机技术的模拟训练自动量化评估优势。Quantitative evaluation is an important part of the simulation training of the Aviation Ammunition technical support.In order to realize the automatic evaluation of the simulation training,intelligent evaluation technology is introduced,and a prediction model based on Sigmoid regression is proposed.On the basis of analyzing the linear relationship of the sample data of the performance indicators,a subset of the characteristic indicators is selected as the input of the prediction mathematical model.In order to avoid the gradient descent method falling into the local solution problem,the gradient descent+PSO algorithm is presented.After testing the result samples,the algorithm can find the global optimal solution under the given precision.The prediction results have no over-fitting and under-fitting problems.In the actual practice,it is no longer necessary to input the subjective results of the examiners and experts,and the advantages of the computer-based simulation training automatic quantitative evaluation are brought into play.

关 键 词：航空弹药 模拟训练 智能评估 粒子群算法 梯度下降法 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]