基于机器学习的直升机侦察效能指标敏感性分析

Helicopter reconnaissance indicators sensitivity analysis based on machine learning

针对直升机侦察效能指标敏感性分析的迫切需求,基于机器学习中的逻辑斯蒂回归方法,提出了一种面向侦察效能的直升机指标敏感性分析方法。首先,介绍了基于机器学习的直升机侦察效能指标敏感性分析的基本步骤;其次,通过任务想定、指标体系构建、相关数据收集、效能评估、机器学习算法的运用进行建模和训练,实现对直升机侦察任务效能的敏感性评估。本研究可以为直升机任务效能敏感分析提供参考,并为直升机在体系中的研发和应用提供更加科学合理的支持。

In order to meet the requirements of sensitivity analysis in the design of helicopter reconnaissance indicators,based on the logistic regression method in machine learning,the reconnaissance capability index system of helicopter system contribution evaluation is established.Firstly,the basic steps of sensitivity analysis of helicopter reconnaissance indicators based on machine learning are introduced.Secondly,sensitivity analysis of helicopter reconnaissance mission effectiveness is achieved through task planning,constructing indicator systems,collecting relevant data,evaluating effectiveness,and using machine learning algorithms for modeling and training.This study can provide reference for the sensitivity analysis of helicopter task efficiency and provide more scientific and reasonable support for the development and application of helicopters in the system.