Neural network dataset, script and model

This data was collected from several sources and compiled into a single text file called NN.txt

Ten quiet and five disturbed days in each month from 2009 to 2019 were used to develop the dataset. These days were got from the list of International Q and D days accessed on the website of the World Data Centre of Geomagnetism, Kyoto (https://wdc.kugi.kyoto-u.ac.jp/qddays/index.html). The dataset has seventeen columns defined as Date, Year (Y), Day of the year (DOY), hour of the day (HH), cosine and sine components of the day of the year for annual variation (DAC and DAS), cosine and sine components of the day of the year for semi-annual variation (DSC and DSS), cosine and sine components of the hour for daily variation (HRC and HRS), geographical coordinates (Lat, Lon), geomagnetic coordinates (Glat, Glon),  Dst Index, F10.7 Index, TEC and sunspot number (SSN). The geographical coordinates were converted to geomagnetic coordinates using quasi dipole coordinates (Emmert et al., 2010; Richmond, 1995). Dst index, F10.7 index, and SSN were downloaded from the OmniWeb database (https://omniweb.gsfc.nasa.gov/form/dx1.html). Jason TEC data was downloaded from the FTP access of the CEDAR Madrigal database (http://cedar.openmadrigal.org/ftp/). 

The data resolution was an 18-second interval. 

It should be noted that any day that had a missing value was eliminated from the database. The data downloaded from Omni web was on a resolution of 1 hour and it was put at an 18-second interval by repeating the same value. The TEC data from the CEDAR Madrigal database is in a second interval and therefore it was averaged at an 18-second interval. 

The dataset was trained with MATLAB software, the MATLAB script (NN script) is attached. The output was a Neural network model also attached