id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
ggj-3345	Palavandishvili, Ana	Supervised Machine Learning in Drought Evaluation	2024	8	.pdf	application/pdf	3191	167	52	By analyzing stations data and satellite sources, it was determined that using the regression method of Machine Learning, it is sufficient to evaluate 1960- 2000 period data for learning and 2001-2022 period data for training. Figure 1 shows a list of stations with insufficient data and whose data were not subjected to statistical analysis A comparison of CHIRPS and station data was made, for which the systematic error (BIAS) was calculated, which refers to the estimation of the difference between the monthly totals of precipitation measured from the satellite and the ground station.	cache/ggj-3345.pdf	txt/ggj-3345.txt