【摘要】 为了评估操作员的功能状态,采用密闭舱空气管理系统模拟多任务过程控制环境,采集了操作员的生理信号,综合操作员主要任务性能和主观评价,建立了操作员功能状态评估模型。同时,提出了一种交叉粒子群优化算法优化自适应模糊神经网络(ANFIS)的参数。试验结果表明,建立的基于交叉粒子群优化算法和ANFIS的操作员功能状态模型能够有效地评估操作员功能状态。更多还原

【Abstract】 In order to assess the functional state of operator,by adopting air management system of airtight cabin,the multi-task process control environment is emulated and the physiological signals of operator are collected.The functional state assessment model for operator is established by integrating operator’s main tasking performance and subjective evaluation.In addition,the cross particle swarm optimization algorithm is proposed to optimize the parameters of the adaptive neural fuzzy inference system(ANFIS).The test result shows that the established operator functional status model based on cross particle swarm optimization algorithm and ANFIS can effectively estimate the functional state of operator.更多还原