Predicting hidden links in supply networks

DOI10.1155/2018/9104387zbMath1390.90132OpenAlexW2787695618MaRDI QIDQ1646525

P. Woodall, A. Brintrup, E. Nicks, W. Krechel, P. Wichmann, Duncan McFarlane

Publication date: 25 June 2018

Published in: Complexity (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2018/9104387

zbMATH Keywords

logistic regressionnaïve Bayesmanufacturing companiesprocurement interdependenciessupply networksupply network link predictor (SNLP) method

Mathematics Subject Classification ID

Stochastic network models in operations research (90B15)

Related Items (1)

Reconstructing production networks using machine learning

Uses Software

• SMOTE

Cites Work

• Unnamed Item
• A new status index derived from sociometric analysis
• A framework for dynamic link prediction in heterogeneous networks

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