Big data-based prediction of terrorist attacks. (July 2019) - Meng, Xi; Nie, Lingyu; Song, Jiapeng
Abstract: An optimised hybrid classifier is proposed for the prediction of terrorist attacks. Hybrid classifier is designed using big data. It puts forward a framework that includes data collection, preprocessing, hybrid classification mining, and classifier testing as a single unit in predicting the terrorist attacks. The genetic algorithm is used to optimise the weight of each single classifier to improve the prediction accuracy of the hybrid classifier. The results reveal that the hybrid classifier is superior to the single classifier in prediction accuracy.