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首页> 外文期刊>International Journal of Environment and Pollution >Fast detection of hazardous organic gases in the ambient air using adaptive neuro-fuzzy inference systems
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Fast detection of hazardous organic gases in the ambient air using adaptive neuro-fuzzy inference systems

机译:使用自适应神经模糊推理系统快速检测环境空气中的有害有机气体

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摘要

In this study, an adaptive neuro-fuzzy inference system (ANFIS) is proposed for the concentration estimation of volatile organic gases before the sensor response time by using the transient sensor response. A neural network (NN) structure with tapped time delays and Mamdani's fuzzy inference system (FIS) are also used for comparison. The e&timation results of ANFIS are better than those of the Mamdani's FIS and much closer to those of the NN. Acceptable performance is obtained for all systems, and the appropriateness of ANFIS for the gas-concentration determination before the sensor response time is observed.
机译:在这项研究中,提出了一种自适应神经模糊推理系统(ANFIS),用于通过使用瞬态传感器响应在传感器响应时间之前估算挥发性有机气体的浓度。具有抽头时间延迟的神经网络(NN)结构和Mamdani的模糊推理系统(FIS)也用于比较。 ANFIS的评估结果优于Mamdani的FIS评估结果,与NN的评估结果更为接近。对于所有系统,都可以获得可接受的性能,并且在观察到传感器响应时间之前,ANFIS是否适合确定气体浓度。

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