操作员功能状态的智能评估

Intelligent Estimating the Functional State of Operator

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。

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.