Energy Conversion and Management X,
Год журнала:
2023,
Номер
19, С. 100396 - 100396
Опубликована: Май 26, 2023
In
the
last
few
years,
energy
efficiency
has
become
a
challenge.
Not
only
mitigating
environmental
impact
but
reducing
waste
can
lead
to
financial
advantages.
Buildings
play
an
important
role
in
this:
they
are
among
biggest
consumers.
So,
finding
manners
reduce
consumption
is
way
minimise
waste,
and
technique
for
that
creating
Demand
Response
(DR)
strategies.
This
paper
proposes
novel
decrease
computational
effort
of
simulating
behaviour
building
using
surrogate
models
based
on
active
learning.
Before
going
straight
problem
building,
which
complex
computationally
costly,
approach
learning
smaller
problem:
with
reduced
simulations,
regress
curve
voltage
versus
current
thermo-resistor.
Then,
implements
model
building.
The
goal
be
able
learn
pattern
limited
number
simulations.
result
given
by
used
set
reference
temperature,
maximising
PV
self-consumption,
usage
from
grid.
Thanks
surrogate,
total
time
spent
map
all
possible
scenarios
around
7
times.
Energy Reports,
Год журнала:
2022,
Номер
9, С. 924 - 940
Опубликована: Дек. 20, 2022
Hybrid
Energy
Systems
(HES)
combine
multiple
energy
sources
to
maximize
efficiency.
Due
the
unpredictability
and
dependence
on
weather,
integrating
renewable
(RES)
is
a
viable
option
for
distributed
distribution
(DG).
To
minimize
environmental
impact
meet
increasing
demand–supply
gap,
scientists
need
find
alternative
sources.
Several
studies
have
confirmed
that
HES
economically
in
remote
areas,
particularly
off-grid
applications.
Despite
several
improvements
over
past
few
years,
existing
control
systems
are
complex,
costly,
less
reliable,
not
sufficiently
efficient.
The
purpose
of
this
paper
present
most
common
challenges
faced
by
stand-alone
hybrid
how
artificial
intelligence
(AI)
technique
has
improved
them.
AI
techniques
widely
used
HES,
study
addressed
can
solve
classification,
forecasting,
networking,
optimization,
problems.
This
provides
an
overview
recent
history
critical
management,
sizing,
demand
side
storage
management;
additionally,
we
conceptual/theoretical
problems,
antecedents,
consequences
may
be
interest
or
require
further
research.
Companies
must
ensure
their
perform
effectively
pay
investments.
Regardless
system,
failures
defects
should
diagnosed
repaired
as
soon
possible.
achieved
system's
efficiency
preventing
early-stage
damage.
Researchers
project
managers
who
work
will
invaluable
resource.
Computational Intelligence and Neuroscience,
Год журнала:
2022,
Номер
2022, С. 1 - 10
Опубликована: Авг. 10, 2022
Corn
has
great
importance
in
terms
of
production
the
field
agriculture
and
animal
feed.
Obtaining
pure
corn
seeds
is
quite
significant
for
seed
quality.
For
this
reason,
distinction
that
have
numerous
varieties
plays
an
essential
role
marketing.
This
study
was
conducted
with
14,469
images
BT6470,
Calipso,
Es_Armandi,
Hiva
types
licensed
by
BIOTEK.
The
classification
carried
out
three
stages.
At
first
stage,
deep
feature
extraction
four
performed
pretrained
CNN
model
SqueezeNet
1000
features
were
obtained
each
image.
In
second
order
to
reduce
these
from
SqueezeNet,
separate
selection
processes
Bat
Optimization
(BA),
Whale
(WOA),
Gray
Wolf
(GWO)
algorithms
among
optimization
algorithms.
Finally,
last
stages
classified
using
machine
learning
methods
Decision
Tree
(DT),
Naive
Bayes
(NB),
multi-class
Support
Vector
Machine
(mSVM),
k-Nearest
Neighbor
(KNN),
Neural
Network
(NN).
mSVM
achieved
highest
success
89.40%.
as
a
result
classifications
through
active
selected
(BA,
WOA,
GWO),
88.82%,
88.72%,
88.95%,
respectively.
accuracies
tested
stage
are
close
other
success.
However,
used
selection,
successful
been
fewer
shorter
time.
results
study,
which
inexpensive,
objective,
time
processing
types,
present
different
perspective
performance.
