基于投影寻踪模型和鱼群算法的新兵军事训练效果评估
CSTR:
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:


Military Training Effect Evaluation of Recruits Based on Projection Pursuit Model and Artificial Fish Swarm Algorithm
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    为科学评估新兵军事训练效果, 针对目前评估中定性评估多、定量评估少、缺乏科学方法和评估标准等 问题进行探讨。通过分析新兵班平均训练数据,构建投影寻踪模型,采用人工鱼群算法解决模型中多约束非线性优 化问题,利用聚类分析对8 个班训练科目成绩进行聚类分析,验证了评价方法的合理性、准确性及评价结果可靠性。 仿真结果表明:该算法模型计算效率高,易操作,为后续开展军事智能化训练提供科学参考依据。

    Abstract:

    In order to evaluate the effect of military training of recruits scientifically, this paper discusses the problems of more qualitative evaluation, less quantitative evaluation and lack of scientific methods and evaluation standards. By analyzing the average training data of recruit classes, constructing projection pursuit model, using artificial fish swarm algorithm to solve the multi-constraint nonlinear optimization problem in the model, and using clustering analysis to cluster the results of eight training classes, the rationality, accuracy and reliability of the evaluation method are verified. The simulation results show that the algorithm model is efficient and easy to operate, and provides a scientific reference for the following intelligent military training.

    参考文献
    相似文献
    引证文献
引用本文

曹 瑾.基于投影寻踪模型和鱼群算法的新兵军事训练效果评估[J].,2021,40(4).

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2020-12-04
  • 最后修改日期:2021-01-14
  • 录用日期:
  • 在线发布日期: 2021-04-15
  • 出版日期:
文章二维码