constructionproductivity {bnRep} | R Documentation |
constructionproductivity Bayesian Network
Description
Construction productivity prediction through Bayesian networks for building projects: case from Vietnam.
Format
A discrete Bayesian network to identify causal relationship and occurrence probability of critical factors affecting construction productivity. Probabilities were given within the referenced paper. The vertices are:
- Accidents
(Yes, No);
- AdverseWeather
(Yes, No);
- Age
(Yes, No);
- Attitude
(Yes, No);
- EngineerQualification
(Yes, No);
- Experience
(Yes, No);
- HealthStatus
(Yes, No);
- MaterialPresence
(Yes, No);
- OwnerFinance
(Yes, No);
- PlanningAndMethod
(Yes, No);
- Productivity
(Yes, No);
- Sex
(Yes, No);
- SkilledWorkers
(Yes, No);
- TaskComplexity
(Yes, No);
- TechnologyLevel
(Yes, No);
- WorkingFrequency
(Yes, No);
- WorkingTools
(Yes, No);
- Workmanship
(Yes, No);
@return An object of class \code{bn.fit}. Refer to the documentation of \code{bnlearn} for details.
References
Khanh, H. D., & Kim, S. Y. (2022). Construction productivity prediction through Bayesian networks for building projects: Case from Vietnam. Engineering, Construction and Architectural Management, 30(5), 2075-2100.
[Package bnRep version 0.0.1 Index]