Machine Learning Models for Generating Synthetic Solar Radiation Data at Cairo, Egypt

The provided data is a part of my PhD thesis, which is concerned with modeling solar radiation components over Cairo, Egypt, using different machine learning algorithms, including: Artificial Neural Networks (MLP, NAR, NARX) Support Vector Machines (SVM) Adaptive Neuro-Fuzzy Inference System (ANFIS) Decision Trees (DT) Random Forest (RF) Gradient Boosting Bagging The model files can be imported and used for forecasting solar radiation using the ML_Predict.m script本数据集为本人博士学位论文的一部分，研究主题为采用多种机器学习算法对埃及开罗地区的太阳辐射分量进行建模，所采用的算法包括：人工神经网络（Artificial Neural Networks，MLP、NAR、NARX）、支持向量机（Support Vector Machines，SVM）、自适应神经模糊推理系统（Adaptive Neuro-Fuzzy Inference System，ANFIS）、决策树（Decision Trees，DT）、随机森林（Random Forest，RF）以及梯度提升装袋法。可通过ML_Predict.m脚本导入模型文件并用于太阳辐射预测任务。