170 related articles for article (PubMed ID: 32834558)
1. Bayesian networks for supply chain risk, resilience and ripple effect analysis: A literature review.
Hosseini S; Ivanov D
Expert Syst Appl; 2020 Dec; 161():113649. PubMed ID: 32834558
[TBL] [Abstract][Full Text] [Related]
2. Ripple effect in the supply chain network: Forward and backward disruption propagation, network health and firm vulnerability.
Li Y; Chen K; Collignon S; Ivanov D
Eur J Oper Res; 2021 Jun; 291(3):1117-1131. PubMed ID: 33071441
[TBL] [Abstract][Full Text] [Related]
3. A comprehensive scoping review of Bayesian networks in healthcare: Past, present and future.
Kyrimi E; McLachlan S; Dube K; Neves MR; Fahmi A; Fenton N
Artif Intell Med; 2021 Jul; 117():102108. PubMed ID: 34127238
[TBL] [Abstract][Full Text] [Related]
4. Prescriptive analytics applications in sustainable operations research: conceptual framework and future research challenges.
Bhatt Mishra D; Naqvi S; Gunasekaran A; Dutta V
Ann Oper Res; 2023 Mar; ():1-40. PubMed ID: 37361099
[TBL] [Abstract][Full Text] [Related]
5. On the relationship between deterministic and probabilistic directed Graphical models: from Bayesian networks to recursive neural networks.
Baldi P; Rosen-Zvi M
Neural Netw; 2005 Oct; 18(8):1080-6. PubMed ID: 16157470
[TBL] [Abstract][Full Text] [Related]
6. Supply chain disruptions and resilience: a major review and future research agenda.
Katsaliaki K; Galetsi P; Kumar S
Ann Oper Res; 2022; 319(1):965-1002. PubMed ID: 33437110
[TBL] [Abstract][Full Text] [Related]
7. Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic.
Golan MS; Jernegan LH; Linkov I
Environ Syst Decis; 2020; 40(2):222-243. PubMed ID: 32837820
[TBL] [Abstract][Full Text] [Related]
8. Causal Datasheet for Datasets: An Evaluation Guide for Real-World Data Analysis and Data Collection Design Using Bayesian Networks.
Butcher B; Huang VS; Robinson C; Reffin J; Sgaier SK; Charles G; Quadrianto N
Front Artif Intell; 2021; 4():612551. PubMed ID: 34337389
[TBL] [Abstract][Full Text] [Related]
9. Increased Use of Bayesian Network Models Has Improved Environmental Risk Assessments.
Moe SJ; Carriger JF; Glendell M
Integr Environ Assess Manag; 2021 Jan; 17(1):53-61. PubMed ID: 33205856
[TBL] [Abstract][Full Text] [Related]
10. Integrating FRAM and BN for enhanced resilience evaluation in construction emergency response: A scaffold collapse case study.
Guo Z; She J; Li Z; Du J; Ye S
Heliyon; 2024 Feb; 10(3):e25342. PubMed ID: 38356520
[TBL] [Abstract][Full Text] [Related]
11. A Review of the Existing and Emerging Topics in the Supply Chain Risk Management Literature.
Pournader M; Kach A; Talluri SS
Decis Sci; 2020 Aug; 51(4):867-919. PubMed ID: 34234385
[TBL] [Abstract][Full Text] [Related]
12. Biological Network Inference With GRASP: A Bayesian Network Structure Learning Method Using Adaptive Sequential Monte Carlo.
Yu K; Cui Z; Sui X; Qiu X; Zhang J
Front Genet; 2021; 12():764020. PubMed ID: 34912373
[TBL] [Abstract][Full Text] [Related]
13. Implementing Bayesian networks for ISO 31000:2018-based maritime oil spill risk management: State-of-art, implementation benefits and challenges, and future research directions.
Parviainen T; Goerlandt F; Helle I; Haapasaari P; Kuikka S
J Environ Manage; 2021 Jan; 278(Pt 1):111520. PubMed ID: 33166738
[TBL] [Abstract][Full Text] [Related]
14. Analysis of resilience strategies and ripple effect in blockchain-coordinated supply chains: An agent-based simulation study.
Lohmer J; Bugert N; Lasch R
Int J Prod Econ; 2020 Oct; 228():107882. PubMed ID: 32834505
[TBL] [Abstract][Full Text] [Related]
15. Blackout and supply chains: Cross-structural ripple effect, performance, resilience and viability impact analysis.
Ivanov D
Ann Oper Res; 2022 Jun; ():1-17. PubMed ID: 35677065
[TBL] [Abstract][Full Text] [Related]
16. OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications.
Ivanov D; Dolgui A
Int J Prod Econ; 2021 Feb; 232():107921. PubMed ID: 32952301
[TBL] [Abstract][Full Text] [Related]
17. Supply chain risk management with machine learning technology: A literature review and future research directions.
Yang M; Lim MK; Qu Y; Ni D; Xiao Z
Comput Ind Eng; 2023 Jan; 175():108859. PubMed ID: 36475042
[TBL] [Abstract][Full Text] [Related]
18. Improving supply chain resilience through industry 4.0: A systematic literature review under the impressions of the COVID-19 pandemic.
Spieske A; Birkel H
Comput Ind Eng; 2021 Aug; 158():107452. PubMed ID: 35313661
[TBL] [Abstract][Full Text] [Related]
19. The future of Cochrane Neonatal.
Soll RF; Ovelman C; McGuire W
Early Hum Dev; 2020 Nov; 150():105191. PubMed ID: 33036834
[TBL] [Abstract][Full Text] [Related]
20. Bayesian Networks for Risk Prediction Using Real-World Data: A Tool for Precision Medicine.
Arora P; Boyne D; Slater JJ; Gupta A; Brenner DR; Druzdzel MJ
Value Health; 2019 Apr; 22(4):439-445. PubMed ID: 30975395
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]