rockquality: rockquality Bayesian Network

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

rockquality Bayesian Network

Description

A probability prediction method for the classification of surrounding rock quality of tunnels with incomplete data using Bayesian networks.

Format

A discrete Bayesian network to predict the probability for the classification of surrounding rock quality of tunnel with incomplete data. Probabilities were given within the referenced paper. The vertices are:

BQ

Basic quality of rock mass (Num1, Num2, Num3, Num4, Num5);

Groundwater

(DryWet, MoistDripping, RainlikeDripping, TubularGushing);

InSituStress

(Low, Medium, High, ExtremelyHigh);

RockHardness

(Hard, SlightlyHard, SlightlySoft, Soft, ExtremelySoft);

RockMassIntegrity

(Complete, SlightlyComplete, SlightlyBroken, Broken, ExtremelyBroken);

RockMassStructure

(State1, State2, State3, State4, State5);

RockQuality

(I, II, III, IV, V);

StructuralPlaneIntegrity

(Good, Ordinary, Bad, VeryBad);

WeatheringDegree

(Fresh, Slight, Medium, Severe, Extreme).

Value

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

References

Ma, J., Li, T., Li, X., Zhou, S., Ma, C., Wei, D., & Dai, K. (2022). A probability prediction method for the classification of surrounding rock quality of tunnels with incomplete data using Bayesian networks. Scientific Reports, 12(1), 19846.

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