Journal of King Saud University - Computer and Information Sciences,
Journal Year:
2023,
Volume and Issue:
35(9), P. 101761 - 101761
Published: Sept. 20, 2023
It
has
been
shown
that
since
the
rapid
development
of
entertainment
industry,
music
generation
become
a
focused
research
topic.
Numerous
methods
for
creating
music,
or
musical
notes
specifically
have
announced,
each
with
distinct
characteristics
and
advantages.
These
usually
concentrated
on
these
two
aspects:
overall
harmony
whole
score
link
between
adjacent
notes,
which
this
referred
respectively
as
general
local
aspects.
This
study
proposes
model
combined
is
capable
deriving
benefits
from
both
aspects,
hence
good
quality
in
terms
quantitative
qualitative
evaluations.
Various
results
based
those
discussed
judged
efficient
enhancing
well
future
opportunities.
The
value
Average
Pitch
Interval
(API)
achieved
remarkable
1.43,
along
note
range
12.145;
while
subjective
aspect,
survey
participants
gave
6.81
generated
yet
only
about
70%
them
can
distinguish
genuine
pieces
music.
AIMS Mathematics,
Journal Year:
2024,
Volume and Issue:
9(8), P. 22321 - 22365
Published: Jan. 1, 2024
<p>Evaluating
behavioral
patterns
through
logic
mining
within
a
given
dataset
has
become
primary
focus
in
current
research.
Unfortunately,
there
are
several
weaknesses
the
research
regarding
models,
including
an
uncertainty
of
attribute
selected
model,
random
distribution
negative
literals
logical
structure,
non-optimal
computation
best
logic,
and
generation
overfitting
solutions.
Motivated
by
these
limitations,
novel
model
incorporating
mechanism
to
control
literal
systematic
Satisfiability,
namely
Weighted
Systematic
2
Satisfiability
Discrete
Hopfield
Neural
Network,
is
proposed
as
structure
represent
behavior
dataset.
For
we
used
ratio
<italic>r</italic>
structures
prevent
solutions
optimize
synaptic
weight
values.
A
new
computational
approach
considering
both
true
false
classification
values
learning
system
was
applied
this
work
preserve
significant
Additionally,
unsupervised
techniques
such
Topological
Data
Analysis
were
ensure
reliability
attributes
model.
The
comparative
experiments
models
utilizing
20
repository
real-life
datasets
conducted
from
repositories
assess
their
efficiency.
Following
results,
dominated
all
metrics
for
average
rank.
ranks
each
metric
Accuracy
(7.95),
Sensitivity
(7.55),
Specificity
(7.93),
Negative
Predictive
Value
(7.50),
Mathews
Correlation
Coefficient
(7.85).
Numerical
results
in-depth
analysis
demonstrated
that
consistently
produced
optimal
induced
represented
performance
study.</p>
AIMS Mathematics,
Journal Year:
2024,
Volume and Issue:
9(2), P. 3711 - 3956
Published: Jan. 1, 2024
<abstract>
<p>The
current
development
of
logic
satisfiability
in
discrete
Hopfield
neural
networks
(DHNN)has
been
segregated
into
systematic
and
non-systematic
logic.
Most
the
research
tends
to
improve
logical
rules
various
extents,
such
as
introducing
ratio
a
negative
literal
flexible
hybrid
structure
that
combines
structures.
However,
existing
rule
exhibited
drawback
concerning
impact
within
structure.
Therefore,
this
paper
presented
novel
class
called
conditional
random
<italic>k</italic>
for
=
1,
2
while
intentionally
disregarding
both
positive
literals
second-order
clauses.
The
proposed
was
embedded
network
with
ultimate
goal
minimizing
cost
function.
Moreover,
non-monotonic
Smish
activation
function
has
introduced
aim
enhancing
quality
final
neuronal
state.
performance
new
compared
other
state
art
conjunction
five
different
types
functions.
Based
on
findings,
obtained
lower
learning
error,
highest
total
neuron
variation
<italic>TV</italic>
857
lowest
average
Jaccard
index,
<italic>JSI</italic>
0.5802.
On
top
that,
highlights
its
capability
DHNN
based
result
improvement
<italic>Zm</italic>
<italic>TV</italic>.
is
consistently
throughout
all
function,
showing
outperforms
functions
terms
<italic>TV.</italic>
This
presents
an
alternative
strategy
mining
technique.
finding
will
be
particular
interest
especially
areas
artificial
network,
function.</p>
</abstract>
AIMS Mathematics,
Journal Year:
2024,
Volume and Issue:
9(5), P. 12090 - 12127
Published: Jan. 1, 2024
<abstract>
<p>Currently,
the
discrete
Hopfield
neural
network
deals
with
challenges
related
to
searching
space
and
limited
memory
capacity.
To
address
this
issue,
we
propose
integrating
logical
rules
into
regulate
neuron
connections.
This
approach
requires
adopting
a
specific
logic
framework
that
ensures
consistently
reaches
lowest
global
energy
state.
In
context,
novel
called
major
1,3
satisfiability
was
introduced.
places
higher
emphasis
on
third-order
clauses
compared
first-order
clauses.
The
proposed
is
trained
by
exhaustive
search
algorithm,
aiming
minimize
cost
function
toward
zero.
evaluate
model
effectiveness,
compare
model's
learning
retrieval
errors
those
of
existing
non-systematic
structure,
which
primarily
relies
similarity
index
measures
benchmark
state
through
extensive
simulation
studies.
Certainly,
random
exhibited
more
solution
when
ratio
exceeds
0.7%
As
experimental
results
other
state-of-the-art
models,
it
became
evident
achieved
significant
in
capturing
overall
These
findings
emphasize
notable
enhancements
performance
capabilities
network.</p>
</abstract>
AIP conference proceedings,
Journal Year:
2024,
Volume and Issue:
3080, P. 040001 - 040001
Published: Jan. 1, 2024
The
sine
and
cosine
algorithm
has
become
a
widely
researched
swarm
optimization
method
in
recent
years
due
to
its
simplicity
effectiveness.
Based
on
the
advantages,
study
this
paper
delves
deeper
into
key
parameters
that
influence
performance
of
algorithm,
implemented
modifications
such
as
integrating
reverse
learning
adding
elite
opposition
solution
create
modified
Sine
Cosine
Algorithm
(the
SCA).
Furthermore,
by
combining
fuzzy
k-nearest
neighbor
with
SCA,
simulates
numeric
datasets
two
or
multiple
classes,
analyzes
results.
accuracy
rate
(ACC)
achieved
SCA
FKNN
is
compared
other
models,
data
comparison
results
tables
presented
for
each.
proposed
obvious
advantages
rate(ACC).
