## 5 Conclusions  
This work was devoted to finding a combination of the latest neural network architectures, which, under specific conditions of TEC variations over three years, according to data from four European stations can provide the most accurate forecast with an advance of 2 h. Of the three selected years, 2015 belonged to the phase of solar activity decline in cycle 24, 2020 had minimal activity during the transition from one cycle to another, and 2022 came to the phase of solar activity increase in cycle 25. According to the annual mean values of TEC and Dst, the year 2022 had higher solar activity than 2015 but lower geomagnetic activity. It is shown that the maximum values of TEC change in accordance with the change in solar activity, which leads to the same trend of changes in the statistical characteristics of the forecast, i.e., the level of solar activity played a greater role than the geomagnetic activity. The use of solar and geomagnetic activity indices is known to affect the accuracy of the TEC forecast; therefore, when choosing the most effective index, estimates were made for a wide set. However, unlike the results presented in [24], a significant contribution of the Vsw index was observed and preliminary calculations were carried out for all architectures for the two sets of parameters, including and excluding the Vsw index as an input parameter. The results for these cases differed markedly; therefore, out of 20 options, only 10 architectures with the best statistical characteristics (with or without Vsw) were selected for presentation. It is significant that among the 10 presented architectures, there are groups of them that provide the same accuracy. So, the traditional LSTM and GRU methods gave estimates [24] at a level corresponding to the literature data. Modifications of the FRF and RFF architecture lines led to a minor increase in accuracy. The use of bidirectional models led to an additional increase in accuracy by a factor of 1.5-2 as compared to these methods. The next group, including BiGRU and BiTCN architectures, provided the lowest errors, i.e., the highest forecasting accuracy. The error estimates for the BiTCN architecture were the best, with less than 0.3 TECU for MAE, less than 0.6 TECU for RMSE, and less than 5% for MAPE. Thus, it was found that the combined use of bidirectional and TCN architectures significantly increases the accuracy of the forecast and levels out the latitudinal dependence. It is planned to apply this approach to 24 h ahead forecasting. Conceptualization, O.M. ; methodology, A.K. and O.M. ; software, A.K. ; validation, O.M. ; formal analysis, A.K. and O.M. ; investigation, A.K. and O.M. ; resources, A.K. ; data curation, O.M. ; writing--original draft preparation, A.K. and O.M. ; writing--review and editing, A.K. and O.M. All authors have read and agreed to the published version of the manuscript. This research was financially supported by the Ministry of Science and Higher Education of the Russian Federation (State task in the field of scientific activity 2023). The OMNI data (F10.7, Np, 10 Kp, Dst, and Vsw indices) were obtained from the GSFC/SPDF OMNIWeb interface at [[https://omniweb.gsfc.nasa.gov](https://omniweb.gsfc.nasa.gov)]([https://omniweb.gsfc.nasa.gov](https://omniweb.gsfc.nasa.gov)) (accessed on 22 January 2022). The data on JPL, GIM, and TEC were obtained from IONEX files located at [[https://urs.earthdata.nasa.gov](https://urs.earthdata.nasa.gov)]([https://urs.earthdata.nasa.gov](https://urs.earthdata.nasa.gov)) (accessed on 10 February 2023). The TEC samples data was obtained from [[https://urs.earthdata.nasa.gov](https://urs.earthdata.nasa.gov)]([https://urs.earthdata.nasa.gov](https://urs.earthdata.nasa.gov)) (accessed on 10 February 2023). Data on solar and geomagnetic activity was taken from SPDF OMNI Web Service [[http://omniweb.gsfc.nasa.gov/form/dxl.html](http://omniweb.gsfc.nasa.gov/form/dxl.html)]([http://omniweb.gsfc.nasa.gov/form/dxl.html](http://omniweb.gsfc.nasa.gov/form/dxl.html)) (accessed on 10 February 2023).