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Systematic methods for knowledge acquisition and expert system development (for combat aircraft)

机译:知识获取和专家系统开发的系统方法(用于战斗机)

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Nine cooperating rule-based systems, collectively called AUTOCREW which were designed to automate functions and decisions associated with a combat aircraft's subsystems, are discussed. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base and to assess the cooperation between the rule bases. Simulation and comparative workload results for two mission scenarios are given. The scenarios are inbound surface-to-air-missile attack on the aircraft and pilot incapacitation. The methodology used to develop the AUTOCREW knowledge bases is summarized. Issues involved in designing the navigation sensor selection expert in AUTOCREW's NAVIGATOR knowledge base are discussed in detail. The performance of seven navigation systems aiding a medium-accuracy inertial navigation system (INS) was investigated using Kalman filter covariance analyses. A navigation sensor management (NSM) expert system was formulated from covariance simulation data using the analysis of variance (ANOVA) method and the ID3 algorithm.
机译:讨论了九种基于规则的协作系统,这些系统统称为AUTOCREW,旨在自动执行与战斗机子系统相关的功能和决策。描述了每个系统内任务的组织;开发了绩效指标以评估每个规则库的工作量并评估规则库之间的合作。给出了两种任务情景的仿真和比较工作量结果。场景是飞机进站地对空导弹袭击和飞行员能力丧失。总结了用于开发AUTOCREW知识库的方法。详细讨论了在AUTOCREW的NAVIGATOR知识库中设计导航传感器选择专家所涉及的问题。使用卡尔曼滤波器协方差分析研究了辅助中等精度惯性导航系统(INS)的七个导航系统的性能。使用方差分析(ANOVA)方法和ID3算法,根据协方差模拟数据制定了导航传感器管理(NSM)专家系统。

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