Abstract: The effect data of actions show a significant randomness because of lots of uncertain elements in the course of action. In order to explore the rules of warfare hidden behind the data, the effectiveness evaluation was studied based on statistical analysis method. The basic concept of action and its effectiveness were analyzed. With the simulation data produced by enhanced irreducible semi-autonomous adaptive combat neural simulation toolkit (EINSTein), a single, a group and multi group experimental methods were used to study the statistical characteristics of offensive actions and find out that to a party who has a combat advantage, compared with increased number of personnel, the increased radius of firepower can achieve better operational results. On this basis, an evaluation method of action effectiveness was proposed and validated with simulation data. Therefore, a feasible resolution is provided to evaluate the action effectiveness based on actual combat data.

Key words: action, effect data, EINSTein tool, statistics, effectiveness evaluation

摘要： 由于作战过程中不确定因素多，作战行动效果数据表现出显著的随机性。为了探索效果数据背后隐藏的作战规律，基于统计分析的方法研究作战行动效能的评估问题。分析了作战行动及其效能的基本概念，针对增强最简半自治适应性作战神经网络工具箱(EINSTein)产生的仿真数据采用单次、单组以及多组实验分析的手段，研究进攻行动效果数据的统计特征，发现对于具有作战优势的一方，相比通过增加作战人数而言，提高火力半径能够取得更好的作战效果。在此基础上，提出一种作战行动效能的评估方法，并结合仿真数据进行了验证，从而为基于实际训练效果数据的效能评估提供可行的解决方案。

关键词: 作战行动, 效果数据, EINSTein工具箱, 统计, 效能评估