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中国兵器工业信息中心, 北京 100089
Received:08 September 2022,
Published Online:12 December 2023,
Published:30 November 2023
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Chiyun LI, Jianming MIAO, Bingzhen SHEN. Operational Effectiveness Prediction of Weapon Equipment System Based on Improved Stacking Ensemble Learning Method[J]. Acta Armamentarii, 2023, 44(11): 3455-3464.
Chiyun LI, Jianming MIAO, Bingzhen SHEN. Operational Effectiveness Prediction of Weapon Equipment System Based on Improved Stacking Ensemble Learning Method[J]. Acta Armamentarii, 2023, 44(11): 3455-3464. DOI: 10.12382/bgxb.2022.0797.
作战效能预测对武器装备体系从建设、生产到实战的全过程都具有重要意义。在Stacking集成学习模型的基础上
优化模型对数据的交叉验证方式
针对原有模型次级学习器输入向量较为稀疏的问题
为次级学习层的输入增加多项式特征和经主成分分析法降维后的各项作战仿真数据指标(原始数据)
形成一种改进Stacking集成学习模型的装备体系作战效能预测方法。以合成营攻占某一阵地的作战效能预测为例
验证该方法的有效性。
Operational effectiveness prediction is a great significance to the weapon equipment system in the whole process from construction
production to actual combat. The cross-validation method for data is optimized based on the Stacking ensemble learning model. For the problem of sparse input vector of secondary learner in the original model
the input polynomial characteristics and the combat simulation data indicators (raw data) after PCA dimension reduction are increased to the learning layer
A prediction method for the operational effectiveness of equipment system with improved Stacking ensemble learning model is proposed. The effectiveness of the method is verified by an example of the operational effectiveness prediction of a synthetic battalion seizing a position.
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