Dynamic resilience analysis of the liner shipping network: From structure to cooperative mechanism
Transportation Research Part E Logistics and Transportation Review,
Год журнала:
2024,
Номер
191, С. 103755 - 103755
Опубликована: Сен. 3, 2024
Язык: Английский
A novel method of assessing port resilience and its positive ramifications
Maritime Policy & Management,
Год журнала:
2025,
Номер
unknown, С. 1 - 24
Опубликована: Янв. 19, 2025
Ports
play
a
crucial
role
in
facilitating
global
trade
and
logistics,
serving
as
vital
hubs
that
connect
countries
continents.
However,
they
are
susceptible
to
disruptions
disasters
due
their
natural
characteristics,
while
resilience
is
essential
for
maintaining
regular
operations,
especially
the
face
of
disruptions.
From
perspective
inputs
outputs,
this
study
evaluates
nine
major
Chinese
ports
from
2011
2021,
using
super-efficiency
slacks-based
measure
network
data
envelopment
analysis
(SBM-NDEA).
This
approach
extends
beyond
evaluating
port's
internal
capacities,
incorporating
urban
economic
factors
critical
ensuring
long-term
resilience.
The
novel
method
assessing
port
its
positive
ramifications
offers
clearer
understanding
specific
stages
requiring
improvement,
thereby
enhancing
overall
ports.
Specifically,
three
considered:
absorptive,
adaptive,
restorative.
results
reveal
different
exhibits
distinct
trends
above
stages.
Shenzhen
Port
demonstrates
superior
performance
both
absorptive
adaptive
stages,
Rizhao
excels
restorative
stage.
research
contributes
advancing
academic
knowledge
industry
practices
by
offering
new
insights,
methodologies,
practical
implications
Язык: Английский
Port resilience to climate change in the Greater Bay Area
Transportation Research Part D Transport and Environment,
Год журнала:
2025,
Номер
unknown, С. 104681 - 104681
Опубликована: Март 1, 2025
Язык: Английский
Traffic complexity assessment on the malacca strait with traffic zone matrix based on AIS data
Ocean Engineering,
Год журнала:
2024,
Номер
314, С. 119687 - 119687
Опубликована: Ноя. 4, 2024
Язык: Английский
Independent operation or coordinated integration? Enhancing the system resilience of ports in dealing with congestion based on a bilateral bargaining game
Ocean & Coastal Management,
Год журнала:
2024,
Номер
259, С. 107437 - 107437
Опубликована: Окт. 25, 2024
Язык: Английский
Port vulnerability to natural disasters: An integrated view from hinterland to seaside
Transportation Research Part D Transport and Environment,
Год журнала:
2024,
Номер
139, С. 104563 - 104563
Опубликована: Дек. 15, 2024
Язык: Английский
Assessing port cluster resilience: Integrating hypergraph-based modeling and agent-based simulation
Transportation Research Part D Transport and Environment,
Год журнала:
2024,
Номер
unknown, С. 104459 - 104459
Опубликована: Окт. 1, 2024
Язык: Английский
Coupling and Coordination Model of Port Resilience and Urban Resilience: A Case Study Guangxi Port City Cluster Along the Pinglu Canal
Lecture notes in civil engineering,
Год журнала:
2024,
Номер
unknown, С. 184 - 193
Опубликована: Ноя. 13, 2024
Язык: Английский
Maritime Traffic Knowledge Discovery via Knowledge Graph Theory
Journal of Marine Science and Engineering,
Год журнала:
2024,
Номер
12(12), С. 2333 - 2333
Опубликована: Дек. 19, 2024
Intelligent
ships
are
a
key
focus
for
the
future
development
of
maritime
transportation,
relying
on
efficient
decision-making
and
autonomous
control
within
complex
environments.
To
enhance
perception,
prediction,
capabilities
these
ships,
present
study
proposes
novel
approach
constructing
time-series
knowledge
graph,
utilizing
real-time
Automatic
Identification
System
(AIS)
data
analyzed
via
sliding
window
technique.
By
integrating
advanced
technologies
such
as
extraction,
representation
learning,
semantic
fusion,
both
static
dynamic
navigational
systematically
unified
graph.
The
specifically
targets
extraction
modeling
critical
events,
including
variations
in
ship
speed,
course
changes,
vessel
encounters,
port
entries
exits.
evaluate
urgency
mathematical
algorithms
applied
to
Distance
Closest
Point
Approach
(DCPA)
Time
(TCPA)
metrics.
Furthermore,
DBSCAN
(Density-Based
Spatial
Clustering
Applications
with
Noise)
clustering
algorithm
is
employed
identify
suitable
docking
berths.
Additionally,
multi-source
meteorological
integrated
data,
providing
more
comprehensive
environment.
resulting
system
effectively
combines
attributes,
status,
event
relationships,
environmental
factors,
thereby
offering
robust
framework
supporting
intelligent
operations.
Язык: Английский