[Submitted on 21 Nov 2024]
View a PDF of the paper titled Predictive Analytics of Air Alerts in the Russian-Ukrainian War, by Demian Pavlyshenko and 1 other authors
Abstract:The paper considers exploratory data analysis and approaches in predictive analytics for air alerts during the Russian-Ukrainian war which broke out on Feb 24, 2022. The results illustrate that alerts in regions correlate with one another and have geospatial patterns which make it feasible to build a predictive model which predicts alerts that are expected to take place in a certain region within a specified time period. The obtained results show that the alert status in a particular region is highly dependable on the features of its adjacent regions. Seasonality features like hours, days of a week and months are also crucial in predicting the target variable. Some regions highly rely on the time feature which equals to a number of days from the initial date of the dataset. From this, we can deduce that the air alert pattern changes throughout the time.
Submission history
From: Bohdan Pavlyshenko [view email]
[v1]
Thu, 21 Nov 2024 22:58:39 UTC (13,699 KB)
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