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

机译：具有抽头时间延迟的神经网络的研究：气体浓度估算

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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：在这项研究中，利用具有延时的人工神经网络（ANN）结构，通过使用瞬态传感器响应来估算传感器响应时间内的甲苯气体浓度。石英晶体微天平（QCM）型传感器用作气体传感器。使用带有IEEE 488卡的计算机控制的测量和自动化系统来控制气体浓度值并收集传感器响应。从瞬态传感器响应趋势中以可接受的良好性能确定甲苯气体浓度，并使用这些训练方法观察到了人工神经网络在传感器响应时间内确定气体浓度的适当性。

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来源
《International Conference on Computational Science and Its Applications(ICCSA 2004) pt.4; 20040514-20040517; Assisi; IT》|2004年|P.398-405|共8页
会议地点 Assisi(IT);Assisi(IT)
作者
Fevzullah Temurtas; Cihat Tasaltin; Hasan Temurtas; Nejat Yumusak; Zafer Ziya Ozturk;
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作者单位

Sakarya University, Department of Computer Engineering, Adapazari, Turkey;

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原文格式 PDF
正文语种 eng
中图分类理论、方法;
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A Study on Neural Networks with Tapped Time Delays: Gas Concentration Estimation

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