基于大数据挖掘的智能指挥控制决策支持模型

Jin Wang, Kun Qin, Xing-seng Li, Hong-liang Gao, Wenjia Lu
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引用次数: 0

摘要

传统辅助决策模型的决策过程存在决策时间长、收敛速度慢的缺点。大数据挖掘技术具有从复杂、多尺度的海量数据中提取或挖掘隐藏有价值信息的特点,且基于人工智能算法的收敛速度快。本文在原有“六库”决策模型的基础上,结合数据挖掘的特点,设计了一种基于深度学习算法的大数据决策支持模型,并对其工作原理和操作流程进行了深入阐述。该过程为指挥员决策提供了一种智能化、信息化的辅助手段,提高了指挥控制决策的实时性和准确性。此外,还讨论了数据挖掘和深度学习算法在指挥控制信息系统中的进一步应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An intelligent Command and Control decision-making support model based on big data mining
The decision-making process of traditional assistant decision-making model has the disadvantages of long decision-making time and slow convergence. Big data mining technology has the characteristics of extracting or mining hidden valuable information from complex and multi-scale massive data, and its convergence speed is fast based on artificial intelligence algorithm. Based on the original “six database” decision model and the characteristics of data mining, this paper designs a big data decision support model based on deep learning algorithm, and deeply expounds its working principle and operation process. This process provides an intelligent and information-based auxiliary means for commanders’ decision-making, and improves the real-time and accuracy of command and control decision-making. In addition, the further application of data mining and deep learning algorithm in command and control information system is also discussed.
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