charleston: charleston Bayesian Network

In bnRep: A Repository of Bayesian Networks from the Academic Literature

charleston Bayesian Network

Description

Parameterization framework and quantification approach for integrated risk and resilience assessments.

Format

A discrete Bayesian network for risk and resilience assessment of climate change impacts within the Charleston Harbor Watershed of South Carolina (Region 3). The probabilities were given within the referenced paper. The vertices are:

AbilityToEvacuate

(Zero, Low, Medium, High);

ActiveHurricane

(No, Yes);

DrowningMortality

(Zero, Low, Medium, High);

EvacuationRequired

(Zero, Low, Medium, High);

ExtremePrecipitation

(Zero, Low, Medium, High);

ExtremePrecipitationNonHurricane

(Zero, Low, Medium, High);

FloodExposure

(Zero, Low, Medium, High);

FloodHazard

(Zero, Low, Medium, High);

FloodPreparedness

(No, Yes);

HurricaneCategory

(Zero, Low, Medium, High);

NuisanceFloodExposure

(Zero, Low, Medium, High);

NuisanceFloodFrequency

(Zero, Low, Medium, High);

NuisanceFloodHazard

(Zero, Low, Medium, High);

PersonalVehicle

(No, Yes);

PhysicalFloodProtection

(No, Yes);

PopulationLocation

(Zero, Low, Medium, High);

RegionWithCoastline

(No, Yes);

RiskToHumanHealth

(Zero, Low, Medium, High);

RoadwayAccessibility

(Zero, Low, Medium, High);

RoadwayLocation

(Zero, Low, Medium, High);

SeaLevelRise

(Zero, Low, Medium, High);

StormSurge

(Zero, Low, Medium, High);

StormSurgeProtection

(No, Yes);

TideLevelAboveHighTide

(Zero, Low, Medium, High);

Value

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

References

Cains, M. G., & Henshel, D. (2021). Parameterization framework and quantification approach for integrated risk and resilience assessments. Integrated Environmental Assessment and Management, 17(1), 131-146.

bnRep documentation built on April 12, 2025, 1:13 a.m.