针对高速公路可变速度控制是一个非线性时变系统，难于用数学模型准确建模这一特点，提出了神经网络控制方法。
The variable speed control for freeway traffic is a nonlinear and time variable system, it is difficult to model with a mathematical model. A neural network control method is put forward.
由此，匝道调节率与可变速度限制间高效的联合控制对于提高道路性能显得尤为重要。
Therefore, an effective combination of ramp metering and variable speed limit control is important to achieve a good performance.
业务层还控制着可变速度标识，车道结束标志和许多可变信息标志。
The operational layer controls also variable speed signs, lane closing symbols and variable message signs.
阐述了神经网络学习算法，设计了高速公路可变速度标志神经网络控制器，并对控制器进行了仿真研究。
The neural network algorithm is formulated and the controller is designed. Simulation research is carried out by taking full advantage of a computer.
在制冷系统控制器确定为低负荷情况时，可变速驱动控制器以运转的较低速度模式操作压缩机马达。
When a low load situation has been determined by the refrigerant system controls, the variable speed drive operates the compressor motor at lower speed mode of operation.
在制冷系统控制器确定为低负荷情况时，可变速驱动控制器以运转的较低速度模式操作压缩机马达。
When a low load situation has been determined by the refrigerant system controls, the variable speed drive operates the compressor motor at lower speed mode of operation.
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