A Quality Evaluation Model of the Digital Armored Force Command Talents Fostering
LIU Zhong-Min 1, 2YE Pei-Jun 3, 4DAI Di 2 WANG Fei-Yue 3, 4
1. University of Chinese Academy of Sciences, Beijing 100190, China 2. Army Academy of Armored Forces, Beijing 100072, China 3. The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China 4. Institute of Intelligent Education, Qingdao Academy of Intelligent Industries, Qingdao Shandong 266109, China
摘要建立基于 BP 神经网络的数字化装甲兵指挥人才培养质量评估模型, 给出人才质量评价指标与培养要素的映射关系,验证基于 BP 神经网络解决非线性人才培养质量评估的技术可行性, 为导入大量数据验证人才培养质量评估模型奠定理论基础. 给出人才培养质量评估结果, 实验结果表明 BP 神经网络能有效地解决人才培养质量评估中的非线性问题, 评估结果准确、稳定,这为人才培养体系构建和辅助决策技术的实现提供技术途径和理论基础.
Abstract：A quality evaluation model for the development of digital armored force command personnel based on BP neural network is established. The relationship between evaluation indicators and development elements for talent quality are given to verify the technical feasibility of solving the nonlinear talent development assessment based on BP neural network, which lays a theoretical foundation for importing a large number of data to verify the algorithm of talent development assessment. The results of talent development assessment are given by validating the data. The experiments show that the BP neural network can effectively solve the non-linear problem accurately and stably in the assessment, which provides a technical approach and theoretical basis for the realization of intelligent talent development assessment and assistant decision-making technology.
刘忠民, 叶佩军, 戴迪, 王飞跃. 数字化装甲兵指挥人才培养质量评估模型[J]. 指挥与控制学报, 2020, 6(4): 388-392.
LIU Zhong-Min, YE Pei-Jun, DAI Di, WANG Fei-Yue. A Quality Evaluation Model of the Digital Armored Force Command Talents Fostering. Journal of Command and Control, 2020, 6(4): 388-392.
2020, Vol. 6 
