[1] D. Yang and J. M. Bright, “Worldwide validation of 8 satellite-derived and reanalysis solar radiation products: A preliminary evaluation and overall metrics for hourly data over 27 years,” Sol. Energy, vol. 210, no. November 2019, pp. 3–19, 2020, doi: 10.1016/j.solener.2020.04.016.
[2] M. Sengupta et al., “Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications,” 2015. [Online]. Available: https://www.nrel.gov/docs/fy15osti/63112.pdf.
[3] R. Perez, R. Seals, and A. Zelenka, “Comparing satellite remote sensing and ground network measurements for the production of site/time specific irradiance data,” Sol. Energy, vol. 60, no. 2, pp. 89–96, 1997, doi: 10.1016/S0038-092X(96)00162-4.
[4] N. Geuder, “Solar Resource Measurements and Satellite Data,” 2013.
[5] I. Karakoti, A. Datta, and S. Singh, “Validation of satellite based solar radiation data with ground measurements,” in Proceedings of the 14th annual international conference and exhibition on geospatial information technology and applica tion, 2012, pp. 1–10.
[6] A. H. Assi, M. H. Al-shamisi, and H. A. N. Hejase, “solar radiation in UAE – a comparison between ground station,” 2012.
[7] B. M. Olomiyesan and O. D. Oyedum, “Comparative Study of Ground Measured, Satellite-Derived, and Estimated Global Solar Radiation Data in Nigeria,” J. Sol. Energy, vol. 2016, pp. 1–7, 2016, doi: 10.1155/2016/8197389.
[8] D. Palmer, E. Koubli, I. Cole, T. Betts, and R. Gottschalg, “Satellite or ground-based measurements for production of site specific hourly irradiance data: Which is most accurate and where?,” Sol. Energy, vol. 165, no. February, pp. 240–255, 2018, doi: 10.1016/j.solener.2018.03.029.
[9] A. Masoom, P. Kosmopoulos, A. Bansal, and S. Kazadzis, “Solar energy estimations in india using remote sensing technologies and validation with sun photometers in urban areas,” Remote Sens., vol. 12, no. 2, pp. 1–25, 2020, doi: 10.3390/rs12020254.
[10] T. Mishra, A. Rabha, U. Kumar, K. Arunachalam, and V. Sridhar, “Assessment of solar power potential in a hill state of India using remote sensing and Geographic Information System,” Remote Sens. Appl. Soc. Environ., vol. 19, no. March 2020, p. 100370, 2020, doi: 10.1016/j.rsase.2020.100370.
[11] V. Manara et al., “Comparison of surface solar irradiance from ground observations and satellite data (1990–2016) over a complex orography region (piedmont—Northwest Italy),” Remote Sens., vol. 12, no. 23, pp. 1–26, 2020, doi: 10.3390/rs12233882.
[12] A. Carpentieri, D. Folini, M. Wild, L. Vuilleumier, and A. Meyer, “Satellite-derived solar radiation for intra-hour and intra-day applications: Biases and uncertainties by season and altitude,” Sol. Energy, vol. 255, no. March, pp. 274–284, 2023, doi: 10.1016/j.solener.2023.03.027.
[13] A. KumarYadav and S. S. Chandel, “Artificial Neural Network based Prediction of Solar Radiation for Indian Stations,” Int. J. Comput. Appl., vol. 50, no. 9, pp. 1–4, 2012, doi: 10.5120/7796-0907.
[14] “Solar Insolation Data,” [Online]. Available: http://www.indiaenvironmentportal.org.in/files/srd-sec.pdf.
[15] A. Mani, Handbook of solar radiation data for India, 1980. 1981.
[16] A. K. Yadav, H. Malik, and S. S. Chandel, “Application of rapid miner in ANN based prediction of solar radiation for assessment of solar energy resource potential of 76 sites in Northwestern India,” Renew. Sustain. Energy Rev., vol. 52, pp. 1093–1106, 2015, doi: 10.1016/j.rser.2015.07.156.
[17] J. Panthee and A. K. Kulchandra, “Estimation of global solar radiation using Artificial Neural Network in Kathmandu, Nepal,” Int. J. Eng. Res. Sci., vol. 2, no. 1, pp. 62–68, 2016.
[18] A. K. Yadav and S. S. Chandel, “Solar energy potential assessment of western Himalayan Indian state of Himachal Pradesh using J48 algorithm of WEKA in ANN based prediction model,” Renew. Energy, vol. 75, pp. 675–693, 2015, doi: 10.1016/j.renene.2014.10.046.
[19] R. Dogra, S. Kumar, and N. Gupta, “Application of Artificial Neural Network to Solar Potential Estimation in Hilly Region of India,” J. Renew. Energy Environ., vol. 9, no. 3, pp. 10–16, 2022, doi: 10.30501/jree.2022.307064.1267.
[20] S. Kumar and T. Kaur, “Efficient solar radiation estimation using cohesive artificial neural network technique with optimal synaptic weights,” Proc. Inst. Mech. Eng. Part A J. Power Energy, vol. 234, no. 6, pp. 862–873, 2020, doi: 10.1177/0957650919878318.
[21] “District environment plan district hamirpur(HP),” Hamirpur (HP), India, 2021. [Online]. Available: https://hphamirpur.nic.in/document/district-environment-plan-hamirpur/.
[22] N. Malhotra and S. Dash, Marketing Research An applied orientation, Seventh. Chennai 600113, Tamil Nadu, India: Pearson India Education Services Pvt. Ltd., 2016.
[23] D. F. Williamson, R. A. Parker, and J. S. Kendrick, “The box plot: A simple visual method to interpret data,” Ann. Intern. Med., vol. 110, no. 11, pp. 916–921, 1989, doi: 10.7326/0003-4819-110-11-916.
[24] K. E. Taylor, “Summarizing multiple aspects of model performance in a single diagram,” J. Geophys. Res., vol. 106, no. D7, pp. 7183–7192, 2001.
[25] S. Gupta et al., “Estimation of Solar Radiation with Consideration of Terrestrial Losses at a Selected Location—A Review,” Sustain., vol. 15, no. 13, pp. 1–29, 2023, doi: 10.3390/su15139962.
[26] M. Suthar, G. K. Singh, and R. P. Saini, “Effects of air pollution for estimating global solar radiation in India,” Int. J. Sustain. Energy, vol. 36, no. 1, pp. 20–27, 2017, doi: 10.1080/14786451.2014.979348.
[27] J. Fan et al., “Evaluating the effect of air
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