Topographic
surveying
and
mapping
is
the
basic
operation
of
waterway
shoreline,
which
plays
an
important
role
in
collection
surface
features,
observation
renovation
buildings,
accumulation
evolution
analysis
data
for
maintenance
observation.
At
present,
technology
drones
very
mature,
but
there
are
still
bottlenecks
flight
time,
power
consumption,
avoidance
flying
obstacles,
affect
results
shoreline.
To
extend
time
this
paper
proposes
a
dynamic
programming
algorithm.
Firstly,
based
on
operations
shoals,
reefs,
height
differences,
siltation
sections
Yangtze
River
waterway,
planning
algorithm
conducted
routes
unmanned
aerial
vehicles.
Divide
path
into
three
segments:
start,
process,
end.
Refine
each
segment
four
items,
construct
Secondly,
analyze
integrate
term
to
eliminate
unsolvable
eigenvalues,
obtain
optimal
effectiveness
verification.
The
indicate
that
dynamically
analyzes
path,
reduces
direction
changes,
improves
vehicles,
shortens
length
overall
consumption
by
adjusting
threshold
process.
With
the
rapid
development
of
computer
technology,
people's
demand
for
information
processing
continues
to
increase.
In
terms
howto
better
store
and
manage
data
with
modern
computing
methods,
scholars
have
begun
focus
on
research
area
limited
scalable,
high-speed
efficient
storage.
Dynamic
programming
algorithm,
as
an
optimization
problem
solving
tool
based
characteristics
continuous
time
series
analysis,
has
attracted
widespread
attention
in
this
field.
This
article
first
introduces
dynamic
theory
related
concepts,
then
tries
determine
optimal
value
connection
between
real-time
indicators
queried
from
static
database
provided
literature
retrieval
results
obtained
historical
queries.
tested
performance
algorithm.
The
test
show
that
algorithm
good
data.
Its
best
calculation
transmission
is
within
3
seconds,
efficiency
range
80%
90%.
integrity
index
above
0.89,
highest
0.97.
five
are
very
close
1.
algorithm's
complete
significant.
Although
provides
in-depth
study
computational
methods
hybrid
blocks,
there
still
areas
improvement.
International Journal of Systems Science,
Год журнала:
2024,
Номер
unknown, С. 1 - 10
Опубликована: Авг. 18, 2024
In
this
paper,
we
investigate
a
continuous-time
linear
quadratic
stochastic
optimal
control
(LQSOC)
problem
in
an
infinite
horizon,
where
diffusion
and
drift
terms
of
the
corresponding
system
depend
on
both
state
variables.
light
theory,
LQSOC
is
reduced
to
solving
generalised
algebraic
Riccati
equation
(GARE).
With
help
existing
model-based
value
iteration
(VI)
algorithm,
propose
two
data-driven
VI
algorithms
solve
GARE.
The
first
one
relies
transforming
into
deterministic
then
by
data
system.
Consequently,
algorithm
does
not
need
information
coefficients
has
lower
complexity.
second
directly
uses
generated
system,
thus
it
circumvents
requirement
all
coefficients.
We
also
provide
convergence
proofs
these
validate
through
simulation
examples.
