A Study on the Occurrence of Crimes Due to Climate Changes Using Decision Tree

  • Jong-Min Kim
  • Hwang-Kwon Ahn
  • Dong-Hwi Lee
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 215)


In this study, we figured out what relationship the elements (weather, temperature, precipitation, wind speed, humidity) of meteorological changes have with the incidence of the five violent crimes through data mining. For the data used in this study, the number of meteorological occurrences from January 1, 2011 to March 30, 2012 through portal sites and the elements of meteorological changes of the day recorded in the Korea Meteorological Administration were used as materials. In this study, an analysis was made using the C4.5 algorithm of decision tree to verify what crimes occur according to the elements of the climate change. As a result of such an analysis, most of the crimes were high in the incidence in the following meteorological conditions: when the weather is cloudy; when the temperature is more than 9 °C; when the precipitation is less than 10 mm; when the wind speed is less than 4 m/s; and the humidity is more than 50 %. Given these meteorological conditions, cloudy weather showed the highest rate of crime incidence.


Decision Tree J48 Algorithm C4.5 Algorithm Crime WEKA 



This work was supported by a grant from Kyonggi university advanced Industrial Security Center of Korea

Ministry of Knowledge Economy


  1. 1.
    Lee Y-H, Kim Y-S (2010) Weather, the day of week, and the number of crime. Association of Criminal PsychologyGoogle Scholar
  2. 2.
    Cheatwood D (2009) Weather and crime. In: Mitchell Miller J (ed.), 21st century criminology: a reference handbook. SAGE Publications, Inc, Thousand Oaks pp 51–58, NcPRAM
  3. 3.
    McLean Iain (2006) Climatic effects on incidence of sexual assault. J Forensic Leg Med 14:16–19CrossRefGoogle Scholar
  4. 4.
    McCleary, R Chew KSY (2002) Winter is the infanticide season: seasonal risk for child homicide. Homicide Stud 6(3):228–239Google Scholar
  5. 5.
    Rotton J, Cohn EG (2000) Weather, disorderly conduct, and assaults: from Scial contact to social avoidance. Environ Behav 32(2):651–673Google Scholar
  6. 6.
    Noh C-H, Cho K-C, Ma Y-B, Lee J-S (2009) Grid resource selection system using decision tree method, Korea Soc Comput Inf 13(1):1–10Google Scholar
  7. 7.
    Leem Y-M, Kwag J-K, Hwang Y-S (2005) A feature analysis of industrial accidents using C4.5 algorithm. Korean Society of SafetyGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Department of Industry SecurityKyonggi UniversitySeoulSouth Korea
  2. 2.Department of Protection & Security ManagementKyonggi UniversitySuwon-siSouth Korea

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