The use of machine learning techniques for assessing the potential of organizational resilience

DOI10.1007/S10100-023-00875-ZMaRDI QIDQ6608506

Buse Çisil Güldoğuş, Süreyya Akyüz, Semih Kuter, Tomasz Ewertowski, Elżbieta Racek, Joanna Sadłowska-Wrzesińska, Gerhard-Wilhelm Weber

Publication date: 20 September 2024

Published in: CEJOR. Central European Journal of Operations Research (Search for Journal in Brave)

zbMATH Keywords

artificial intelligenceregressionmachine learningdecision-making processorganizational resilience

Mathematics Subject Classification ID

Operations research and management science (90Bxx)

Cites Work

• Bagging predictors
• CMARS: a new contribution to nonparametric regression with multivariate adaptive regression splines supported by continuous optimization
• On numerical optimization theory of infinite kernel learning
• Estimation of dependences based on empirical data. Transl. from the Russian by Samuel Kotz
• Multivariate adaptive regression splines
• Long-term load forecasting: models based on MARS, ANN and LR methods
• RMARS: robustification of multivariate adaptive regression spline under polyhedral uncertainty
• Fuzzy and robust approach for decision-making in disaster situations
• Infinite kernel learning via infinite and semi-infinite programming
• The elements of statistical learning. Data mining, inference, and prediction
• Random forests
• The use of spatial data mining methods for modeling HR challenges of generation Z in greater Poland region

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