Data Aggregation and Terror Group Prediction using Machine Learning Algorithms
S P Maniraj1, Deep Chaudhary2, Vankayala Hari Deep3, Vishesh Pratap Singh4
1S P Maniraj, Assistant Professor (Senior Grade), Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
2Deep Chaudhary, Student B.Tech, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
3Vankayala Hari Deep, Student B.Tech, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
4Vishesh Pratap Singh, Student B.Tech, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.

Manuscript received on November 15, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on November 30, 2019. | PP: 1467-1479 | Volume-8 Issue-4, November 2019. | Retrieval Number: D7590118419/2019©BEIESP | DOI: 10.35940/ijrte.D7590.118419

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: This paper is about to introduce a proposed system that examines growth or decay of the terrorist groups by the time, active locations, types of attack they carry out, motive targets, Weapon mastery and availability and many parameters to analyze the patterns and hidden structures in their activity and to predict the occasion and type of their future attack. We have done a detailed analysis of data we get from different sources and we also performed different classification algorithms on the available data to find the chances of probable attack on different regions.Based on results finding which of the algorithms works with highest accuracy.
Keywords: Analysis, Classification, Prediction, Terrorism, Data Aggregation, Terror Group.
Scope of the Article: Machine Learning.