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Dynamic Forecasting Conditional Probability of Bombing Attacks Based on Time-Series and Intervention Analysis
- Source :
- Risk Analysis. 37:1287-1297
- Publication Year :
- 2016
- Publisher :
- Wiley, 2016.
-
Abstract
- In recent years, various types of terrorist attacks occurred, causing worldwide catastrophes. According to the Global Terrorism Database (GTD), among all attack tactics, bombing attacks happened most frequently, followed by armed assaults. In this article, a model for analyzing and forecasting the conditional probability of bombing attacks (CPBAs) based on time-series methods is developed. In addition, intervention analysis is used to analyze the sudden increase in the time-series process. The results show that the CPBA increased dramatically at the end of 2011. During that time, the CPBA increased by 16.0% in a two-month period to reach the peak value, but still stays 9.0% greater than the predicted level after the temporary effect gradually decays. By contrast, no significant fluctuation can be found in the conditional probability process of armed assault. It can be inferred that some social unrest, such as America's troop withdrawal from Afghanistan and Iraq, could have led to the increase of the CPBA in Afghanistan, Iraq, and Pakistan. The integrated time-series and intervention model is used to forecast the monthly CPBA in 2014 and through 2064. The average relative error compared with the real data in 2014 is 3.5%. The model is also applied to the total number of attacks recorded by the GTD between 2004 and 2014.
- Subjects :
- 021110 strategic, defence & security studies
Series (stratigraphy)
Engineering
Social unrest
business.industry
0211 other engineering and technologies
Conditional probability
Poison control
02 engineering and technology
Computer security
computer.software_genre
01 natural sciences
010104 statistics & probability
Intervention analysis
Global terrorism
Physiology (medical)
Terrorism
Statistics
Peak value
0101 mathematics
Safety, Risk, Reliability and Quality
business
computer
Subjects
Details
- ISSN :
- 02724332
- Volume :
- 37
- Database :
- OpenAIRE
- Journal :
- Risk Analysis
- Accession number :
- edsair.doi...........56c67938e76e5b19ee63356857c6fc79