George
Mohler       
   












George
Tita   
        

SCU
Mathematics     
   












UCI
Criminology
Jeff Br...
    Certain
crime
types
show
an
elevated
risk
of
crime
     following
an
event

  Retaliation
is
a
cause
of
inter‐gang
violence
  Burglars
return
to
the
same,
or
neighboring,
  house
in
the
days/weeks...
Hawkes Processmodel adaptedfrom seismology
  Each
day
fit
the
Hawkes
Process
to
past
data
  to
estimate
risk
level
across
the
city
  Direct
patrols
to
highest
risk
...
Prototype Software wI GoogleMaps Interface           ~      University of                                                 ...
P= 0.0207                                   P=0.0199              Pveh = 0.702, Pres = 0 .297                      Pveh = ...
  Patrol
efficiency:

quantitative
approach
to
  placing
patrols
where
crime
is
located
  Reduction
in
crime
rate
in
flagge...
UC MaSC           Mathematical and Simulation            Modeling of Crime  NSF
Human
Social
Dynamics
Program
  NSF
Divi...
Upcoming SlideShare
Loading in …5
×

Система предсказания преступлений

655 views

Published on

Система предсказания преступлений (Santa Cruz Police Department, Калифорния)

Published in: Education, Travel
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
655
On SlideShare
0
From Embeds
0
Number of Embeds
4
Actions
Shares
0
Downloads
2
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Система предсказания преступлений

  1. 1. George
Mohler 
 












George
Tita 
 

SCU
Mathematics 
 












UCI
Criminology
Jeff Brantingham Santa Cruz Police DeptUCLA Anthropology Los Angeles Police Dept
 UC MaSC Mathematical And Simulation Modeling of Crime
  2. 2.   Certain
crime
types
show
an
elevated
risk
of
crime
 following
an
event

  3. 3.   Retaliation
is
a
cause
of
inter‐gang
violence
  Burglars
return
to
the
same,
or
neighboring,
 house
in
the
days/weeks
after
a
crime
 “I always go back [to the same places] because, once you been there, you know just about when you been there before and when you can go back. An every time I hit a house, it’s always on the same day [of the week] I done been before cause I know there ain’t nobody there. “ (Subject No. 51) Wright and Decker Burglars on the Job
  4. 4. Hawkes Processmodel adaptedfrom seismology
  5. 5.   Each
day
fit
the
Hawkes
Process
to
past
data
 to
estimate
risk
level
across
the
city
  Direct
patrols
to
highest
risk
areas
and
times
 of
day
  Next
day
recalibrate
model
and
repeat
   As
highest
risk
areas
change,
the
model
and
 patrols
adapt

  6. 6. Prototype Software wI GoogleMaps Interface ~ University of CabnUo Hwy G) california Santa Cruz • Harvey We1>t Park ~ ~ Soquel Ave TWin Lakes e ry co .9. Lagoon Park ~ "",....f ",Y ~ • ~ Q <s- , If) -< ~ • atural BrIdges Slele Beach en ~ u" ~Or L i~ouse • Field Slate Beach
  7. 7. P= 0.0207 P=0.0199 Pveh = 0.702, Pres = 0 .297 Pveh = 1, Pres = O TW : 13 : 00, 15 : 00 TW : 12 : 00, 13 : 00 200 Laurel 51P is probability of one or more crimes in 24 hour time periodPveh, Pres are conditional probabilities of vehicular and residential crimeTW gives start times of 2 highest risk 1-hour time windows
  8. 8.   Patrol
efficiency:

quantitative
approach
to
 placing
patrols
where
crime
is
located
  Reduction
in
crime
rate
in
flagged
areas

 Reduction
in
overall
crime
rate

  9. 9. UC MaSC Mathematical and Simulation Modeling of Crime  NSF
Human
Social
Dynamics
Program
  NSF
Division
of
Mathematical
Sciences
  US
DoD,

ARO,
AFOSR,
ONR
  Santa
Clara
University,
UCLA,
UC
Irvine
  LAPD,
Long
Beach
PD,
Santa
Cruz
PD
publications:
paleo.sscnet.ucla.edu


×