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An Intelligent Weather Station

机译:智能气象站

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摘要

Accurate measurements of global solar radiation, atmospheric temperature and relative humidity, as well as the availability of the predictions of their evolution over time, are important for different areas of applications, such as agriculture, renewable energy and energy management, or thermal comfort in buildings. For this reason, an intelligent, light-weight, self-powered and portable sensor was developed, using a nearest-neighbors (NEN) algorithm and artificial neural network (ANN) models as the time-series predictor mechanisms. The hardware and software design of the implemented prototype are described, as well as the forecasting performance related to the three atmospheric variables, using both approaches, over a prediction horizon of 48-steps-ahead.
机译:准确测量全球太阳辐射,大气温度和相对湿度,以及获得其随时间演变的预测,对于农业,可再生能源和能源管理或建筑物的热舒适性等不同应用领域都至关重要。 。因此,使用最近邻(NEN)算法和人工神经网络(ANN)模型作为时间序列预测器机制,开发了一种智能,轻便,自供电和便携式传感器。描述了已实现原型的硬件和软件设计,以及在提前48步的预测范围内使用这两种方法与三个大气变量相关的预测性能。

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