Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences,
Journal Year:
2021,
Volume and Issue:
379(2194), P. 20200093 - 20200093
Published: Feb. 15, 2021
Machine
learning
(ML)
provides
novel
and
powerful
ways
of
accurately
efficiently
recognizing
complex
patterns,
emulating
nonlinear
dynamics,
predicting
the
spatio-temporal
evolution
weather
climate
processes.
Off-the-shelf
ML
models,
however,
do
not
necessarily
obey
fundamental
governing
laws
physical
systems,
nor
they
generalize
well
to
scenarios
on
which
have
been
trained.
We
survey
systematic
approaches
incorporating
physics
domain
knowledge
into
models
distill
these
broad
categories.
Through
10
case
studies,
we
show
how
used
successfully
for
emulating,
downscaling,
forecasting
The
accomplishments
studies
include
greater
consistency,
reduced
training
time,
improved
data
efficiency,
better
generalization.
Finally,
synthesize
lessons
learned
identify
scientific,
diagnostic,
computational,
resource
challenges
developing
truly
robust
reliable
physics-informed
This
article
is
part
theme
issue
‘Machine
modelling’.
IEEE Access,
Journal Year:
2020,
Volume and Issue:
8, P. 21980 - 22012
Published: Jan. 1, 2020
Digital
twin
can
be
defined
as
a
virtual
representation
of
physical
asset
enabled
through
data
and
simulators
for
real-time
prediction,
optimization,
monitoring,
controlling,
improved
decision
making.
Recent
advances
in
computational
pipelines,
multiphysics
solvers,
artificial
intelligence,
big
cybernetics,
processing
management
tools
bring
the
promise
digital
twins
their
impact
on
society
closer
to
reality.
twinning
is
now
an
important
emerging
trend
many
applications.
Also
referred
megamodel,
device
shadow,
mirrored
system,
avatar
or
synchronized
prototype,
there
no
doubt
that
plays
transformative
role
not
only
how
we
design
operate
cyber-physical
intelligent
systems,
but
also
advance
modularity
multi-disciplinary
systems
tackle
fundamental
barriers
addressed
by
current,
evolutionary
modeling
practices.
In
this
work,
review
recent
status
methodologies
techniques
related
construction
mostly
from
perspective.
Our
aim
provide
detailed
coverage
current
challenges
enabling
technologies
along
with
recommendations
reflections
various
stakeholders.
The Innovation,
Journal Year:
2021,
Volume and Issue:
2(4), P. 100179 - 100179
Published: Oct. 29, 2021
•"Can
machines
think?"
The
goal
of
artificial
intelligence
(AI)
is
to
enable
mimic
human
thoughts
and
behaviors,
including
learning,
reasoning,
predicting,
so
on.•"Can
AI
do
fundamental
research?"
coupled
with
machine
learning
techniques
impacting
a
wide
range
sciences,
mathematics,
medical
science,
physics,
etc.•"How
does
accelerate
New
research
applications
are
emerging
rapidly
the
support
by
infrastructure,
data
storage,
computing
power,
algorithms,
frameworks.
Artificial
promising
(ML)
well
known
from
computer
science
broadly
affecting
many
aspects
various
fields
technology,
industry,
even
our
day-to-day
life.
ML
have
been
developed
analyze
high-throughput
view
obtaining
useful
insights,
categorizing,
making
evidence-based
decisions
in
novel
ways,
which
will
promote
growth
fuel
sustainable
booming
AI.
This
paper
undertakes
comprehensive
survey
on
development
application
different
information
materials
geoscience,
life
chemistry.
challenges
that
each
discipline
meets,
potentials
handle
these
challenges,
discussed
detail.
Moreover,
we
shed
light
new
trends
entailing
integration
into
scientific
discipline.
aim
this
provide
broad
guideline
sciences
potential
infusion
AI,
help
motivate
researchers
deeply
understand
state-of-the-art
AI-based
thereby
continuous
sciences.
Remote Sensing,
Journal Year:
2020,
Volume and Issue:
12(19), P. 3136 - 3136
Published: Sept. 24, 2020
Agriculture
provides
for
the
most
basic
needs
of
humankind:
food
and
fiber.
The
introduction
new
farming
techniques
in
past
century
(e.g.,
during
Green
Revolution)
has
helped
agriculture
keep
pace
with
growing
demands
other
agricultural
products.
However,
further
increases
demand,
a
population,
rising
income
levels
are
likely
to
put
additional
strain
on
natural
resources.
With
recognition
negative
impacts
environment,
approaches
should
be
able
meet
future
while
maintaining
or
reducing
environmental
footprint
agriculture.
Emerging
technologies,
such
as
geospatial
Internet
Things
(IoT),
Big
Data
analysis,
artificial
intelligence
(AI),
could
utilized
make
informed
management
decisions
aimed
increase
crop
production.
Precision
(PA)
entails
application
suite
technologies
optimize
inputs
production
reduce
input
losses.
Use
remote
sensing
PA
increased
rapidly
few
decades.
unprecedented
availability
high
resolution
(spatial,
spectral
temporal)
satellite
images
promoted
use
many
applications,
including
monitoring,
irrigation
management,
nutrient
application,
disease
pest
yield
prediction.
In
this
paper,
we
provide
an
overview
systems,
techniques,
vegetation
indices
along
their
recent
(2015–2020)
applications
PA.
Remote-sensing-based
variable
fertilizer
rate
technology
Seeker
Crop
Circle
have
already
been
incorporated
commercial
unmanned
aerial
vehicles
(UAVs)
tremendously
last
decade
due
cost-effectiveness
flexibility
obtaining
high-resolution
(cm-scale)
needed
applications.
At
same
time,
large
amount
data
prompted
researchers
explore
advanced
storage
processing
cloud
computing
machine
learning.
Given
complexity
image
technical
knowledge
expertise
needed,
it
is
critical
develop
simple
yet
reliable
workflow
real-time
Development
accurate
easy
use,
user-friendly
systems
result
broader
adoption
non-commercial
