An attempt to promote intelligent petroleum processing: a look at how different programming languages works with deep learning models for gasoline quality detection
Research Square (Research Square),
Год журнала:
2024,
Номер
unknown
Опубликована: Май 21, 2024
Abstract
The
current
study
explores
how
several
programming
languages
affect
deep
learning
models
for
gasoline
quality
detection,
highlighting
the
significance
of
choosing
best
appropriate
language
according
to
project
needs.
Featuring
scientific
computations
using
an
integrated
development
environment
Visual
Studio
Code
(VS
Code)
tool.
This
work
has
reached
multiple
outcomes:
Python
is
known
its
rapid
and
adaptability,
which
are
well-suited
exploring
control
techniques
in
petroleum
products.
Java
recognized
stability
flexibility
across
many
platforms,
making
it
ideal
large-scale
deployments
that
require
dependable
performance
refinery
equipment.
C/C++
lauded
speed
ability
manage
hardware
resources
effectively,
essential
real-time
production
settings,
allowing
quick
analysis
little
delay
processes.
utilizes
a
architecture
Java,
C,
Python,
with
frameworks
such
as
aid
model
construction,
goal
creating
flexible
tools
monitoring
dynamic
Язык: Английский
Does using Bazel help speed up continuous integration builds?
Empirical Software Engineering,
Год журнала:
2024,
Номер
29(5)
Опубликована: Июль 19, 2024
Язык: Английский