Advances in chemical and materials engineering book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 354 - 369
Published: May 31, 2024
This
study
embarks
on
a
novel
exploration
of
integrating
renewable
power
sources,
particularly
wind
and
solar
energy,
into
edible
devices,
focusing
the
Indian
grid's
context.
As
prevalence
energy
sources
grows,
dynamics
systems
are
rapidly
evolving,
presenting
unique
challenges
such
as
network
stability
fluctuating
outputs.
research
specifically
addresses
variability
inherent
in
investigates
potential
minimum
variable
rate
pumped
storage
to
provide
fundamental
consistency
grids.
Key
issues
inertia
minimization
posed
by
nano-grids
examined,
with
an
emphasis
their
impact
devices.
The
also
explores
use
rapid
dispatchable
generation
(DG)
units,
like
Kenneth
configurable
speed
hydel
charger,
viable
solutions
fluctuation
typical
renewable-rich
systems.
Advances in systems analysis, software engineering, and high performance computing book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 168 - 188
Published: June 28, 2024
The
present
research
studies
the
optimization
of
multipass
milling
parameters
for
AISI
304
stainless
steel,
adopting
a
systematic
experimental
technique
based
on
Taguchi
L9
array
design.
methodically
adjusts
cutting
speed,
feed
rate,
and
depth
cut,
documenting
their
impacts
surface
roughness.
Experimental
data,
obtained
with
Mitutoyo
portable
tester,
are
foundation
training
machine
learning
models.
linear
regression
(LR)
model,
trained
using
1200
measurements,
produces
prediction
equation
remarkable
accuracy
92.335%,
offering
insights
into
correlations
between
machining
Concurrently,
an
artificial
neural
network
(ANN)
exhibiting
100%
accuracy,
captures
non-linear
patterns
inherent
in
process.
actual
vs.
anticipated
values
table
LR
model
further
demonstrate
its
predictive
powers.
Advances in systems analysis, software engineering, and high performance computing book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 239 - 256
Published: June 30, 2024
In
this
research,
the
integration
of
meta-heuristic
optimization
into
health
monitoring
systems
is
explored
for
its
transformative
potential.
The
study
employs
a
comprehensive
evaluation
approach,
focusing
on
Performance
Metrics,
Resource
Utilization,
and
Scalability
Testing.
Results
indicate
consistently
high
level
accuracy
(90%
to
97%)
swift
response
times
(125
165
milliseconds),
highlighting
reliability
efficiency
enhanced
system.
Utilization
demonstrates
optimal
memory
CPU
usage
(110
130
MB
30%
47%,
respectively),
underscoring
sustainable
balanced
operation
Testing
reveals
system's
adaptability
changes
in
user
numbers
data
complexity,
with
ranging
from
150
200
milliseconds.
Meta-heuristic
emerges
as
key
enabler,
fine-tuning
predictive
capabilities,
optimizing
resource
usage,
ensuring
seamless
scalability.
Advances in systems analysis, software engineering, and high performance computing book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 341 - 358
Published: June 30, 2024
This
study
investigates
the
application
of
simulation-driven
metaheuristic
algorithms
to
enhance
agricultural
operations,
specifically
focusing
on
their
effectiveness
and
efficiency
in
addressing
complexities
modern
systems.
evaluates
computational
efficacy
crop
planning,
resource
allocation,
decision-making
using
a
simulation
environment
tailored
for
contexts.
Efficiency
parameters,
such
as
execution
time,
convergence
rate,
scalability,
offer
valuable
insights
into
algorithms'
real-world
Effectiveness
evaluation
analyze
quality,
resilience,
variety
proposed
techniques,
demonstrating
potential
react
changing
environmental
circumstances.
Statistical
analysis
is
employed
give
proof
observed
variances
performance,
hence
providing
quantitative
aspect
evaluation.
Advances in systems analysis, software engineering, and high performance computing book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 323 - 340
Published: June 30, 2024
In
this
paper,
we
explore
the
application
of
Particle
Swarm
Optimization
(PSO)
to
maximize
performance
Wavelength
Division
Multiplexing
(WDM)
networks
by
optimizing
optical
fiber
paths.
Through
rigorous
evaluation
metrics
such
as
Data
Transmission
Speed
Analysis
and
Congestion
Reduction
Assessment
across
ten
trials,
our
findings
reveal
consistent
meaningful
improvements.
PSO
effectively
enhances
data
transfer
speeds,
resulting
more
efficient
network
performance.
Moreover,
approach
reliably
minimizes
congestion
levels,
decreasing
a
significant
challenge
in
WDM
networks.
These
results
highlight
PSO's
adaptability
reliability
solving
challenging
optimization
challenges
communication.
The
practical
reveals
its
promise
revolutionary
tool
for
attaining
higher
speeds
reliability,
providing
basis
future
breakthroughs
communication
Advances in systems analysis, software engineering, and high performance computing book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 1 - 18
Published: June 30, 2024
This
study
studies
the
implementation
of
machine
learning
(ML)
algorithms
to
improve
power
distribution
in
an
industrial
context,
concentrating
on
essential
issue
anticipating
energy
consumption.
Various
ML
models,
including
Support
Vector
Machine
(SVM),
Artificial
Neural
Network
(ANN),
Decision
Trees
(DT),
and
Random
Forests
(RF),
were
extensively
examined
compared
for
their
usefulness
demand
patterns
within
a
sector
encompassing
machining,
forging,
CNC,
packaging
stations.
The
models
revealed
various
strengths,
with
SVM
leading
accuracy
95.6%,
closely
followed
by
ANN
at
94.33%,
while
DT
RF
displayed
accuracies
87.6%
85.6%,
respectively.
research
additionally
gives
thorough
comparison
actual
vs
expected
levels
over
hourly
intervals,
illustrating
models'
responsiveness
dynamic
use
throughout
day.
Advances in systems analysis, software engineering, and high performance computing book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 49 - 66
Published: June 30, 2024
This
study
explores
the
integration
of
machine
learning
techniques,
notably
Support
Vector
Machines
(SVM)
and
Convolutional
Neural
Networks
(CNN),
with
industrial
production
processes
for
quality
assurance.
The
emphasis
is
on
examining
performance
SVM
CNN
through
a
rigorous
assessment
precision,
recall,
F1
score
in
Performance
Metrics
Evaluation.
Additionally,
tests
algorithms
against
existing
baseline
approaches,
evaluating
their
accuracy
efficiency
fault
identification.
results
reveal
consistent
strong
CNN,
highlighting
revolutionary
potential
revolutionizing
control
systems.
findings
provide
essential
insights
into
properties
each
algorithm,
demonstrating
ability
to
outperform
methods
contribute
more
versatile
efficient
approach
assurance
settings.
Advances in systems analysis, software engineering, and high performance computing book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 143 - 167
Published: June 28, 2024
In
the
search
for
sustainable
and
reliable
energy
solutions,
deployment
of
hybrid
renewable
systems
(HRES)
has
developed
as
a
promising
approach
mainly
powering
remote
villages
that
lack
access
to
centralized
grids.
The
optimal
configuration
these
leads
complex
optimization
problem
through
demanding
application
meta-heuristic
algorithms
efficiently
direct
massive
solution
space
recognize
most
cost-effective
setup.
Numerous
have
been
engaged
this
purpose.
Through
comparative
analysis
various
algorithms,
particle
swarm
helps
in
obtaining
improved
solutions.
Particle
(PSO)
occurs
powerful
effective
technique
addressing
task
determining
configurations
positioned
villages.
Advances in systems analysis, software engineering, and high performance computing book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 302 - 329
Published: June 28, 2024
Operational
cost
savings
in
electric
utilities
using
the
application
of
genetic
algorithms
power
system
planning
and
operation
characterize
an
innovative
approach
that
involves
computational
intelligence
to
optimize
complex
decision-making
processes
grid
functioning.
Electric
involve
various
challenges
which
managing
generation,
transmission
distribution
are
necessary
meet
ever-growing
demand
for
electricity
with
reduction
operational
costs.
These
overcome
aid
a
algorithm.
In
field
planning,
engaged
configuration
expansion
distribution.
Advances in systems analysis, software engineering, and high performance computing book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 85 - 105
Published: June 28, 2024
In
this
research
endeavor,
the
laser
welding
of
C63000
alloy
has
been
thoroughly
examined,
focusing
on
interplay
key
parameters—laser
power,
speed,
and
amplitude.
The
experimental
design,
structured
as
per
Taguchi
L9
array,
provided
a
systematic
approach
to
investigating
these
parameters'
effects
critical
mechanical
properties,
specifically
tensile
strength
Brinell
hardness.
alloy's
responses
were
meticulously
studied
under
varied
conditions,
capturing
nuances
its
behavior
in
response
changes
inputs.
outcomes
revealed
distinct
trends
hardness
relation
variations
parameters.
Notably,
highest
levels
consistently
observed
specific
combinations
Advances in systems analysis, software engineering, and high performance computing book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 254 - 273
Published: June 28, 2024
This
work
presents
a
holistic
framework
for
automating
automated
guided
vehicles
(AGVs)
in
industrial
settings
by
using
well-positioned
sensors
and
sophisticated
machine
learning
models.
The
AGV
is
put
through
rigorous
testing
along
variety
of
pathways.
It
outfitted
with
such
as
wheel
encoders,
proximity
sensors,
ultrasonic
LIDAR.
Microcontrollers
the
high-speed
electronic
system
enable
real-time
data
processing
decision-making
based
on
sensor
inputs.
For
purpose
anticipating
impediments
maximising
routes,
models
decision
trees
(DT),
artificial
neural
networks
(ANN),
support
vector
machines
(SVM),
random
forests
(RF)
are
developed
assessed.
Experiments
showing
accuracy,
F1
score,
precision,
recall
show
how
well
integrated
is.
prime
example
effective
route
planning,
obstacle
avoidance,
navigation
busy
settings.
