AI,
Journal Year:
2024,
Volume and Issue:
5(4), P. 1977 - 2017
Published: Oct. 25, 2024
Various
Artificial
Intelligence
(AI)
techniques
in
water
resource
management
highlight
the
current
methodologies’
strengths
and
limitations
forecasting,
optimization,
control.
We
identify
a
gap
integrating
these
diverse
approaches
for
enhanced
prediction
management.
critically
analyze
existing
literature
on
artificial
neural
networks
(ANNs),
deep
learning
(DL),
long
short-term
memory
(LSTM)
networks,
machine
(ML)
models
such
as
supervised
(SL)
unsupervised
(UL),
random
forest
(RF).
In
response,
we
propose
novel
framework
that
synergizes
into
unified,
multi-layered
model
incorporates
digital
twin
multi-modal
transformer
approach.
This
integration
aims
to
leverage
collective
advantages
of
each
method
while
overcoming
individual
constraints,
significantly
enhancing
accuracy
operational
efficiency.
paper
sets
foundation
an
innovative
twin-integrated
solution,
focusing
reviewing
past
works
precursor
detailed
exposition
our
proposed
subsequent
publication.
advanced
approach
promises
redefine
demand
forecasting
contribute
global
sustainability
efficiency
use.
International Journal of Systems Science,
Journal Year:
2022,
Volume and Issue:
54(1), P. 204 - 235
Published: Dec. 16, 2022
Slime
Mould
Algorithm
(SMA)
has
recently
received
much
attention
from
researchers
because
of
its
simple
structure,
excellent
optimisation
capabilities,
and
acceptable
convergence
in
dealing
with
various
types
complex
real-world
problems.
this
study
aims
to
retrieve,
identify,
summarise
analyse
critical
studies
related
SMA
development.
Based
on
this,
98
SMA-related
the
Web
Science
were
retrieved,
selected,
identified.
The
two
main
review
vectors
advanced
versions
SMAs
application
domains.
First,
we
counted
analysed
SMAs,
summarised,
classified,
discussed
their
improvement
methods
directions.
Secondly,
sort
out
domains
role,
development
status,
shortcomings
each
domain.
A
survey
based
existing
literature
shows
that
clearly
outperform
some
established
metaheuristics
terms
speed
accuracy
handling
benchmark
problems
solving
multiple
realistic
optimization
This
not
only
suggests
possible
future
directions
field
but,
due
inclusion
graphical
tabular
comparisons
properties,
also
provides
a
comprehensive
source
information
about
SAMs
scope
adaptation
for
Sustainability,
Journal Year:
2021,
Volume and Issue:
13(13), P. 7448 - 7448
Published: July 2, 2021
Solving
the
optimal
power
flow
problems
(OPF)
is
an
important
step
in
optimally
dispatching
generation
with
considered
objective
functions.
A
single-objective
function
inadequate
for
modern
systems,
required
high-performance
generation,
so
problem
becomes
multi-objective
(MOOPF).
Although
MOOPF
has
been
widely
solved
by
many
algorithms,
new
solutions
are
still
to
obtain
better
performance
of
generation.
Slime
mould
algorithm
(SMA)
a
recently
proposed
metaheuristic
that
applied
solve
several
optimization
different
fields,
except
problem,
while
it
outperforms
various
algorithms.
Thus,
this
paper
proposes
solving
based
on
SMA
considering
cost,
emission,
and
transmission
line
loss
as
part
functions
system.
The
IEEE
30-,
57-,
118-bus
systems
used
investigate
problems.
values
generated
compared
those
other
algorithms
literature.
simulation
results
show
provides
than
literature,
Pareto
fronts
presenting
can
be
efficiently
obtained.
Mathematical Biosciences & Engineering,
Journal Year:
2022,
Volume and Issue:
19(3), P. 2240 - 2285
Published: Jan. 1, 2022
<abstract>
<p>The
slime
mould
algorithm
(SMA)
is
a
metaheuristic
recently
proposed,
which
inspired
by
the
oscillations
of
mould.
Similar
to
other
algorithms,
SMA
also
has
some
disadvantages
such
as
insufficient
balance
between
exploration
and
exploitation,
easy
fall
into
local
optimum.
This
paper,
an
improved
based
on
dominant
swarm
with
adaptive
t-distribution
mutation
(DTSMA)
proposed.
In
DTSMA,
used
SMA's
convergence
speed,
balances
enhanced
exploitation
ability.
addition,
new
mechanism
hybridized
increase
diversity
populations.
The
performances
DTSMA
are
verified
CEC2019
functions
eight
engineering
design
problems.
results
show
that
for
functions,
best;
problems,
obtains
better
than
many
algorithms
in
literature
when
constraints
satisfied.
Furthermore,
solve
inverse
kinematics
problem
7-DOF
robot
manipulator.
overall
strong
optimization
Therefore,
promising
global
problems.</p>
</abstract>
