系统仿真学报 ›› 2023, Vol. 35 ›› Issue (3): 525-533.doi: 10.16182/j.issn1004731x.joss.21-1016

• 论文 • 上一篇    下一篇

关键人物的决策行为建模方法研究

郑潇1(), 彭晓东1(), 鲁敏育2, 刘铁军3   

  1. 1.中国科学院国家空间科学中心,北京 100190
    2.61646部队,北京 100192
    3.75833部队,广东 广州 510510
  • 收稿日期:2021-09-30 修回日期:2022-03-08 出版日期:2023-03-30 发布日期:2023-03-22
  • 通讯作者: 彭晓东 E-mail:zhengxiao@nssc.ac.cn;pxd@nssc.ac.cn
  • 作者简介:郑潇(1992-),女,助理研究员,硕士,研究方向为重要目标行为预测。E-mail:zhengxiao@nssc.ac.cn

Research on Decision Behavior Modeling Method of Key Figures

Xiao Zheng1(), Xiaodong Peng1(), Minyu Lu2, Tiejun Liu3   

  1. 1.National Space Science Center Chinese Academy of Sciences, Beijing 100190, China
    2.PLA 61646 Troops, Beijing 100192, China
    3.PLA 75833 Troops, Guangzhou 510510, China
  • Received:2021-09-30 Revised:2022-03-08 Online:2023-03-30 Published:2023-03-22
  • Contact: Xiaodong Peng E-mail:zhengxiao@nssc.ac.cn;pxd@nssc.ac.cn

摘要:

关键人物的决策是影响重要事件演化发展的重要因素,对其决策行为的研究对于重要事件的预测有着重要意义。面向关键人物的决策行为建模及决策倾向性预判问题,分析了人物建模所需的特征要素及特征测量方法,分析了人物决策过程及决策关联影响要素,开展了决策倾向性预测方法探索研究,构建了综合利益特征及心理特征的决策行为倾向性预测模型。通过开展关键人物的决策行为建模方法研究,模拟人面对问题事件的决策习惯,为事件发展方向的预判探索一种新方法。

关键词: 关键人物, 事件预判, 决策行为建模, 决策倾向性预测

Abstract:

The decision-making of key figures is an important factor affecting the evolution of concerned events. The research on their decision-making behavior is of great significance for the prediction of important events. For the problem of decision behavior modeling and decision propensity prediction of key figures, the character attribute and measurement methods required for character modeling are analyzed, the character decision-making process and decision-making related influencing factors are analyzed, the exploration research of decision propensity prediction method is carried out, and the prediction model of decision propensity based on comprehensive interest characteristics and psychological characteristics is constructed. Through the research on the modeling method of key figures' decision-making behavior, this paper simulates people's decision-making habits in the face of crucial events, and explores a novel method for predicting the development direction of events.

Key words: key figures, events prediction, decision-making behavior modeling, decision-making propensity prediction

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