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首页> 外文期刊>Journal of Engineering & Applied Sciences >Artificial Neural Networks Modeling of Relation Relaying Daily Global Solar Radiation to Astronomical and Meteorological Parameters
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Artificial Neural Networks Modeling of Relation Relaying Daily Global Solar Radiation to Astronomical and Meteorological Parameters

机译:人工神经网络与天文和气象参数的日常全球太阳辐射相关联

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摘要

Algeria naturally has a significant solar potential. This qualitative constant favors the exploitation and development of this energy resource. However, the use of this energy requires knowledge of the potential of solar radiation on horizontal and inclined planes. In fact, the objective of this study is to develop a neural model that can be used to predict the daily global solar radiation average received on a horizontal surface. Several models using different meteorological and astronomical parameters were studied in order to choose the most efficient model based on error between real and predicted irradiation. The results indicate that the model using as input variables: azimuth, zenith angle, extraterrestrial solar radiation, relative humidity, precipitation and wind speed is the most efficient among the studied models.
机译:阿尔及利亚自然具有显着的太阳能潜力。 这种定性持续有利于这种能源资源的开发和发展。 然而,这种能量的使用需要了解水平和倾斜平面上的太阳辐射的潜力。 事实上,本研究的目的是开发一种神经模型,可用于预测在水平表面上接收的日常全球太阳辐射平均值。 研究了使用不同气象和天文参数的若干模型,以便根据真实和预测辐射之间的误差选择最有效的模型。 结果表明,使用作为输入变量的模型:方位角,天顶角,外星式太阳辐射,相对湿度,降水量和风速是研究中最有效的模型。

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