Prediction of Political and Local Conflicts in Bangladesh: An Event Analysis

The international communities are trying to establish a comprehensive, precise, and valuable early warning system for conflict prevention involving political and local riots for many decades. The field of machine learning has some potential and promising components to develop this type of system. To...

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Bibliographic Details
Published in2021 International Conference on Science & Contemporary Technologies (ICSCT) pp. 1 - 6
Main Authors Hasan, H M Mahmudul, Ahnaf, Adil, Hossain, Nahid
Format Conference Proceeding
LanguageEnglish
Published IEEE 05.08.2021
Subjects
Bangladesh
Conflict Analysis
Data models
Geology
Performance evaluation
Political and Local
Prediction
Prediction algorithms
Predictive models
Training
Urban areas
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Summary:The international communities are trying to establish a comprehensive, precise, and valuable early warning system for conflict prevention involving political and local riots for many decades. The field of machine learning has some potential and promising components to develop this type of system. To predict and efficiently analyze all political conflicts in Bangladesh is the main motive of this paper. This study focuses on the time and geolocation of the conflict events, learning the event pattern, and predicting future conflicts in such areas. This study used the Naive Bayes algorithm to create a dataset blueprint that was later trained with Random Forrest to make a prediction model and used Tableau to map geolocations of predicting data for visualization. This study shows satisfactory results with 94.84 per cent accuracy. The dataset is available at https://tinyurl.com/hs9vxnu
DOI:10.1109/ICSCT53883.2021.9642517