使用贝叶斯网络建模在应用多INT监控环境中的决策支持系统的评估
Mary E Frame1, Barbara Acker-Mills1, Anna Maresca1
1Research and Development Department, Parallax Advanced Research, Beavercreek, Ohio.
概括
决策支持系统 (DSS) 通过帮助感知和预测来改善情报分析. 与口头标签相比,DSS中的数字概率显示提高了分析师的准确性和速度.
科学领域:
- 认知科学 认知科学
- 情报分析 情报分析
- 决策支持系统是什么?
背景情况:
- 在情报,监视和侦察 (ISR) 中,感知和决策对于预测敌对事件至关重要.
- 分析师在长时间内整合多个来源的信息,需要强大的心理模型来准确预测.
- 通过自动化复杂的计算和提供建议,探索决策支持系统 (DSS) 来增强分析师的决策.
研究的目的:
- 评估两个模拟决策支持系统 (DSS) 作为预测辅助工具的有效性.
- 评估DSS对情报分析速度和准确性的影响.
- 为了比较数字和口头概率显示在DSS中的有效性.
主要方法:
- 参与者参与了一个模拟的多天,多源情报任务.
- 两个由贝叶斯网络模型提供信息的DSS与对照组进行了测试.
- 参与者每天对五种潜在结果进行预测.
主要成果:
- 使用DSS的参与者比对照组更快地实现了正确的解决方案.
- 使用DSS增加了36-44%的参与者达到正确结论的比例.
- 在DSS中的数值概率显示在区分不太可能的结果方面优于口头标签.
结论:
- 决策支持系统显著提高了情报分析的效率和准确性.
- 在DSS中的数值概率表示提高了对低概率事件的辨别能力.
- DSS,特别是数字显示器,为智能感知和预测提供了宝贵的进步.
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