The codes and dataset for paper Estimation of Global Horizontal Irradiance in China Using A Deep Learning Method

This file includes the dataset and codes as well. All the programs are run on MATLAB, only the trained model and data are provided. The deep learning package used is deebnet (deep belief networks) toolbox in MATLAB and octave v3.2 disclosed by M. A. keyvanrad and M. M. homayounpour, which can be found in http://ceit.aut.ac.ir/~keyvanrad/DeeBNet Toolbox.html DownloadThis test needs to download the software package first.1. Ready to run environment1). Input "addpath ('deebnet ') in the command line window of MATLAB to indicate the introduction of the software package.2). Enter "load ('dbn) on the command line_ for_ ghi.mat '), load the trained deep training model. You will see that three kinds of DBNs correspond to clearday / icecloud / watercloud respectively.2. Only input parameter data after processing is provided. The step of how to convert satellite image into input parameter file is omitted.3. First execute to compute GHI. M and then run convertoraster. M. It is recommended to run the code in blocks instead of directly executing the whole file.See readme and code Notes for details.