Abstract In this study, an adaptive neuro-fuzzy inference system (ANFIS) model is proposed for the prediction of daily diffuse solar radiation. Eight factors including month of the year, sunshine duration, barometric pressure, relative humidity, mean temperature, wind speed, rainfall and daily global solar radiation are used as the inputs, while the daily diffuse solar radiation is the output. To compare the performance of the ANFIS, artificial neural network (ANN) and Iqbal models, two statistical benchmark indices, root-mean-squared error (RMSE) and coefficient of determination (R2), are adopted in this study. The results show that the proposed ANFIS model has potential in accurately predicting the daily diffuse solar radiation.

中文翻译：

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使用自适应神经模糊推理系统技术估计每日漫射太阳辐射

摘要 在这项研究中，提出了一种自适应神经模糊推理系统（ANFIS）模型来预测日漫射太阳辐射。以月份、日照时长、气压、相对湿度、平均温度、风速、降雨量和每日全球太阳辐射8个因素作为输入，而每日漫射太阳辐射为输出。为了比较 ANFIS、人工神经网络 (ANN) 和 Iqbal 模型的性能，本研究采用了两个统计基准指标，均方根误差 (RMSE) 和确定系数 (R2)。结果表明，提出的ANFIS模型具有准确预测日漫射太阳辐射的潜力。