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INTELLIGENT RECEPTOR MODELLING: A RECEPTOR MODELLING BASED ON ADAPTIVE TECHNIQUES

机译:智能受体建模:基于自适应技术的受体建模

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A receptor modeling was implemented using artificial neural networks as a weight tool of the contributions of different sources in the emission of particulate matter to the atmosphere. The performance of the neural network was considerably improved using genetic algorithms which is responsible for a fine-tuning of the modeling. The whole system is controlled by a set of fuzzy rules. The characterization of the particulate matter was made using PIXE, Mossbauer spectroscopy, X-ray diffractometry, thermogravimetric analysis, scanning electron microscope and complimentary techniques. The obtained information from this characterization is the basis of the intelligent receptor modeling.
机译:使用人工神经网络实施受体建模,作为不同来源在气氛中排放颗粒物质中的不同来源的贡献的重量工具。使用遗传算法,神经网络的性能大大提高,该遗传算法负责造型的微调。整个系统由一组模糊规则控制。使用Pixe,莫斯贝尔光谱,X射线衍射测定,热重分析,扫描电子显微镜和互补技术进行颗粒物质的表征。来自该表征的所获得的信息是智能受体建模的基础。

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