STORM CASUALTIES
INTRODUCTION
T deadl ar becoming a
con f the humans the
USA.
T stor aff the li of th
of USA in diff .
T accur pr about t
condit can hel in
the casualt r in the USA.
PROJECT
SCOPE
E data
the occurr of
in the USA.
A of the storm
occu in the USA
(J , 2017).
C and anal detailed
r to deadl
in the USA.
IMPORTANCE
OF THE
PROJECT
T r in the st e leading deaths in
USA is a g concer .
T high fr the st in the USA
storm casualt .
T casualties diff to pr (J ,
2017).
T storm also pr on
due to the in the
e .
OBJECTIVES
T m objectives
•T determine possibili deadly can
casualties the nation.
•T identify false relating storms.
•T lower the of storm (J , 2017).
DATASET
DESCRIPTION
T dataset have used the NWS NOAA
data of 2017.
•S
•F
•L
DATASET 1:
STORM
DETAILS
T prim data in the .
T storm as:
•T number ty of storm
•D and ti
•P
•I the storm .
•T data set 51 56,921 cases.
DATASET 2: FATALITIES
I , 2017 .
•T :
•A
•G
•D
•L
•T 11 775 .
DATASET 3:
LOCATIONS
T third is . T variables the dataset
•T location
•R of the
•D
•T dataset 11 43,579 .
DATA
TECHNIQUES
•T visualizations T were used which
geospatial and ti series.
•T geospatial shows the sta are prone
.
•T tim series highlights of the ye in which
is chances of .
GEOSPATIAL MAP AND TIME SERIES
DATA
TECHNIQUES:
CONTD.
A technique the text visualization
use R.
•F predictive were used.
T predictive used the study :
•N network
•R forest
•L
•S (SVM)
•H that com NN, SVM,
.
LESSONS LEARNED
•A .
•B .
•C .
•E .
CONCLUSION
•D USA.
•H .
•D , , .
•C .
•L .
REFERENCES
•J , D. (2017, S 24). I 2017 the hur season ? T .
R J 11, 2022, http://time. /4952628/hur e- n- y-
a- e-
•NOAA/NWS pr r. A F T Summar - NOAA/NWS
S Pr C r. (2021). R J 11, 2022,
://www. .noaa.g /climo/tor /f .
