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脑力负荷的准确预测是研究装甲车辆乘员信息处理作业的关键技术,对提高人机系统设计的合理性具有重要意义。为有效解决应急任务条件下装甲车辆乘员信息处理作业的脑力负荷预测问题,针对装甲车辆乘员作业向信息处理作业转变的基本趋势,结合信息处理作业操作元模型和认知图式分析,基于信息执行通道任务-网络建模方法构建了脑力负荷预测模型,量化了工作资源参数,并面向目标录入典型信息处理作业对预测模型进行了实例应用。结果表明:该模型能够清晰地描述装甲车辆乘员信息处理作业脑力负荷变化情况,有效地找出脑力负荷异常的时间节点和产生原因,量化预测作业各时刻脑力负荷,具有较好的预测精度和可重用性。
The accurate prediction of mental workload is the key technology to study the information processing of armored vehicle occupants. It is of great significance to improve the rationality of human-computer system design. In order to effectively solve the problem of mental load forecasting of armored vehicle occupant information processing under emergency task conditions and to deal with the basic trend of armored vehicle occupant operation to information processing operation transformation combined with the information processing operation operating element model and cognitive schema analysis, Channel task-network modeling method constructs the mental load forecasting model, quantifies the working resource parameters, and applies the typical forecasting model to target-oriented typical information processing jobs. The results show that the model can clearly describe the changes of the mental workload of armored vehicle occupant information processing operations, identify the time nodes and causes of the abnormal mental workload effectively, and quantify the mental workload at each moment of the forecasting operation with good prediction accuracy. Reusability.