Learn R Programming

bnRep (version 0.0.3)

arcticwaters: arcticwaters Bayesian Network

Description

An object-oriented Bayesian network model for the quantitative risk assessment of navigational accidents in ice-covered Arctic waters.

Arguments

Value

An object of class bn.fit. Refer to the documentation of bnlearn for details.

Format

A discrete Bayesian network for the quantitative risk assessment of multiple navigational accidents in ice-covered Arctic waters. Probabilities were given within the referenced paper. The vertices are:

AidNavigationFailure

(No, Yes);

AirTemperature

(<0 degrees, >0 degrees);

C_BesettingInIce

(Significant, Severe, Catastrophic);

C_Collision

(Significant, Severe, Catastrophic);

C_Grounding

(Significant, Severe, Catastrophic);

C_ShipIceCollision

(Significant, Severe, Catastrophic);

ChannelDepth

(Inadequate, Adequate);

ChartUpdating

(No, Yes);

CommunicationEquipmentFailure

(No, Yes);

DriftIce

(No, Yes);

EnvironmentalObstacles

(No, Yes);

Fatigued

(No, Yes);

Fog

(No, Yes);

GrossTonnage

((0,500], (500,3000], (3000,10000], >10000);

IceConcentration

(<3/10, 4/10-6/10, >7/10);

IceCondition

(Poor, Good);

IceStrength

(Low, Medium, High);

IceThickness

(<0.5m, >0.5m);

IceType

(Thin Ice, Medium Ice, Old Ice);

InadequateKnowledge

(No, Yes);

JudgmentFailure

(No, Yes);

LackCommunication

(No, Yes);

LackSafetyMeasures

(No, Yes);

LackSituationalAwareness

(No, Yes);

MechanicalEquipmentFailure

(No, Yes);

NavigatorFailure

(No, Yes);

Negligence

(No, Yes);

P_BesettingInIce

(No, Yes);

P_Collision

(No, Yes);

P_Grounding

(No, Yes);

P_ShipIceCollision

(No, Yes);

PowerFailure

(No, Yes);

PropellerFailure

(No, Yes);

RadarFailure

(No, Yes);

Rain

(No, Yes);

SeaCurrent

(No, Yes);

SeaTemperature

(<0 degrees, >0 degrees);

ShipType

(Oil Tanker, General Cargo Ship, Passenger Ship, Icebreaker, Others);

SteeringFailure

(No, Yes);

StrongWind

(No, Yes);

UnsafeAct

(No, Yes);

UnsafeCondition

(No, Yes);

UnsafeSpeed

(No, Yes);

Visibility

(Poor, Good);

WaterwayCondition

(Poor, Good);

WeatherCondition

(Poor, Good);

References

Fu, S., Zhang, Y., Zhang, M., Han, B., & Wu, Z. (2023). An object-oriented Bayesian network model for the quantitative risk assessment of navigational accidents in ice-covered Arctic waters. Reliability Engineering & System Safety, 238, 109459.