Water,
Год журнала:
2024,
Номер
16(23), С. 3450 - 3450
Опубликована: Ноя. 30, 2024
Vermicomposting
is
one
of
the
most
important
waste
management
techniques
in
process
vermiculture.
In
this
study,
a
neural
network-assisted
novel
paradigm
proposed
to
predict
from
vermicomposting.
The
network
skeleton
based
on
gallium
arsenide
processing
schema,
which
used
separate
wastes.
By
comparing
system
with
existing
methods,
it
was
found
that
approach
had
highest
average
prediction
ratio
91.32%,
outperforming
other
like
encoder-recurrent
decoder
(ERD)
network,
recurrent
(RNN),
and
deep
long
short-term
memory
(deep
LSTM)
network.
separation
analysis
also
demonstrated
effectiveness
method,
range
45–94%.
Furthermore,
study
emphasizes
importance
chemical
equilibrium
our
schema
achieving
high
accuracies,
showcasing
its
potential
for
practical
application
processes.
Lastly,
evolution
stages
detailed,
indicating
efficiency
various
levels
separation.
Overall,
provides
valuable
insights
into
methods
optimizing
wastewater
processes,
paving
way
more
effective
sustainable
vermicomposting
practices.
The
potential
benefits
of
bioconversion
commercial
broiler
poultry
litter
(PL)
to
vermicompost
(with
Eudrilus
eugeniae)
were
studied
by
optimizing
the
carbon-nitrogen
ratio
(C/N)
using
coconut
(Cocos
nucifera)
coir
pith
(CP)
and
farm
yard
manure
(FM)
as
co-substrate.
In
this
experiment,
after
C/N
at
levels
25,
30,
35,
pre-composting
PL
followed
vermicomposting
was
done,
FM
alone
used
control
group.
After
pre-composting,
earthworms
(Eudrilus
introduced,
process
continued
for
90
days
samples
analyzed
on
45th
90th
days.
study
revealed
a
significantly
(P
Water,
Год журнала:
2024,
Номер
16(23), С. 3450 - 3450
Опубликована: Ноя. 30, 2024
Vermicomposting
is
one
of
the
most
important
waste
management
techniques
in
process
vermiculture.
In
this
study,
a
neural
network-assisted
novel
paradigm
proposed
to
predict
from
vermicomposting.
The
network
skeleton
based
on
gallium
arsenide
processing
schema,
which
used
separate
wastes.
By
comparing
system
with
existing
methods,
it
was
found
that
approach
had
highest
average
prediction
ratio
91.32%,
outperforming
other
like
encoder-recurrent
decoder
(ERD)
network,
recurrent
(RNN),
and
deep
long
short-term
memory
(deep
LSTM)
network.
separation
analysis
also
demonstrated
effectiveness
method,
range
45–94%.
Furthermore,
study
emphasizes
importance
chemical
equilibrium
our
schema
achieving
high
accuracies,
showcasing
its
potential
for
practical
application
processes.
Lastly,
evolution
stages
detailed,
indicating
efficiency
various
levels
separation.
Overall,
provides
valuable
insights
into
methods
optimizing
wastewater
processes,
paving
way
more
effective
sustainable
vermicomposting
practices.
