firerisk {bnRep} | R Documentation |
firerisk Bayesian Network
Description
Predictive study of fire risk in building using Bayesian networks.
Format
A discrete Bayesian network to calculate the probability of fire ignition in buildings (root nodes were given a uniform distribution). The probabilities were available from a repository. The vertices are:
- A1
Deficient electrical installation (T, F);
- A2
Bad quality of electical equipment (T, F);
- A3
Contact between incompatible products (T, F);
- B1
Mishandling of electrical devices (T, F);
- B2
Electrical overload (T, F);
- B3
Power cut (T, F);
- B4
Degradation of electrical wires (T, F);
- B5
Excessive heating in the conductors (T, F);
- B6
Insulation fault (T, F);
- B7
Short circuit (T, F);
- B8
Strong intensity electric (T, F);
- B9
Combustion of electrical equipment (T, F);
- B10
Appearance of electric arcs (T, F);
- B11
Appearence of sparks (T, F);
- B12
Chemical reactions (T, F);
- B13
Heat release (T, F);
- B14
Appearance of new products (T, F);
- C1
Electrical equipment malfunction (T, F);
- C2
Electrocution (T, F);
- C3
Fire ignition (T, F);
- C4
Poisoning (T, F);
- C5
Asphyxia (T, F);
- C6
Explosion (T, F);
Value
An object of class bn.fit
. Refer to the documentation of bnlearn
for details.
References
Issa, S. K., Bakkali, H., Azmani, A., & Amami, B. (2024). Predictive study of fire risk in building using Bayesian networks. Journal of Theoretical and Applied Information Technology, 102(7).