This paper proposes a dynamic Bayesian network to represent the cause-and-effect relationships in an industrial supply chain. Based on the Quick Scan, ...
This paper proposes a dynamic Bayesian network to represent the cause-and-effect relationships in an industrial supply chain. Based on the Quick Scan, ...
This paper proposes a dynamic Bayesian network to represent the cause-and-effect relationships in an industrial supply chain.
This paper deals with production and inventory control using a Dynamic Bayesian Network, a probabilistic model which represents the qualitative dependence ...
Dynamic Bayesian networks can be utilized as a knowledge base of the reasoning systems where the diagnostic tasks are conducted. We finally solve this reasoning ...
This paper proposes a dynamic Bayesian network to represent the cause-and-effect relationships in an industrial supply chain. Based on the Quick Scan, ...
Feb 25, 2022 · This study develops a fuzzy dynamic Bayesian network (FDBN) in which fuzzy variables as well as crisp variables are considered. The proposed ...
The paper describes a key material supply forecasting diagnostics tools based on Dynamic. Bayesian Network (DBN). The tool was embodied parametric ...
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Apr 1, 2022 · This would transform the current Bayesian network approach into a dynamic. Bayesian network, which would better suit the data and overall ...
Oct 22, 2024 · Dynamic Bayesian network (DBN) theory provides a valid tool to estimate the risk of disruptions, propagating along the supply chain (SC), ...