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A Study on Neural Networks with Tapped Time Delays: Gas Concentration Estimation

机译:跨越时间延迟神经网络研究:气体浓度估计

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In this study, an artificial neural network (ANN) structure with tapped time delays is used for the concentration estimation of Toluene gas inside the sensor response time by using the transient sensor response. The Quartz Crystal Microbalance (QCM) type sensors were used as gas sensors. A computer controlled measurement and automation system with IEEE 488 card was used to control the gas concentration values and to collect the sensor responses. The determination of Toluene gas concentrations from the trend of the transient sensor responses achieved with acceptable good performances, and the appropriateness of the artificial neural network for the gas concentration determination inside the sensor response time is observed with these training methods.
机译:在该研究中,通过使用瞬态传感器响应,使用具有旋转时间延迟的人工神经网络(ANN)结构用于传感器响应时间内的甲苯气体的浓度估计。石英晶体微稳定(QCM)型传感器用作气体传感器。使用IEEE 488卡的计算机控制测量和自动化系统用于控制气体浓度值并收集传感器响应。通过这些训练方法观察到从实现的瞬态传感器响应所达到瞬态传感器响应的趋势的测定,以及用于传感器响应时间内的气体浓度测定的人工神经网络的适当性。

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