Forecasting and Anomaly Detection in BEWS: Comparative Study of Theta, Croston, and Prophet Algorithms
Forecasting,
Год журнала:
2024,
Номер
6(2), С. 343 - 356
Опубликована: Май 21, 2024
Evaluation
of
water
quality
and
accurate
prediction
pollution
indicators
are
key
components
in
resource
management
control.
The
use
biological
early
warning
systems
(BEWS),
which
living
organisms
used
as
biosensors,
allows
for
a
comprehensive
assessment
the
aquatic
environment
state
timely
response
event
an
emergency.
In
this
paper,
we
examine
three
machine
learning
algorithms
(Theta,
Croston
Prophet)
to
forecast
bivalves’
activity
data
obtained
from
BEWS
developed
by
authors.
An
algorithm
anomalies
detection
was
developed.
Our
results
showed
that
one
anomalies,
Prophet
best
method,
other
two,
anomaly
time
did
not
differ
between
methods.
A
comparison
methods
terms
computational
speed
advantage
method.
This
can
be
effectively
incorporated
into
software
systems,
facilitating
rapid
responses
changes
environment.
Язык: Английский
Using the Contrast Boundary Concentration of LST for the Earthquake Approach Assessment in Turkey, 6–8 February 2023
Earth,
Год журнала:
2024,
Номер
5(3), С. 388 - 403
Опубликована: Авг. 18, 2024
Land
surface
temperature
(LST)
variations
and
anomalies
associated
with
tectonic
plate
movements
have
been
documented
before
large
earthquakes.
In
this
work,
we
propose
that
spatially
extended
dynamic
linear
zones
of
high
at
the
Earth’s
coinciding
faults
in
crust
may
be
used
as
a
predictor
an
approaching
earthquake.
LST
contrast
boundary
concentration
maps
are
suggested
to
possible
indicator
for
analyzing
changes
after
seismic
sequences.
Here,
analyze
boundaries
estimated
from
Landsat
8–9
data
East
Anatolian
Fault
Zone
vicinity
epicenters
destructive
earthquakes
magnitudes
up
7.8
Mw
occurred
February
2023.
A
spatial
relationship
between
earthquake
maximum
azimuths
0°
90°
was
found
strengthen
approaches
weaken
it.
It
92%
located
5
km
distance
concentration.
The
evidence
presented
work
supports
idea
provide
valuable
information
hazard
assessment
Язык: Английский