Hybrid Gaussian Process and Bayesian Network Inference for Explainable Decision Support in Industrial Systems
Computing Conference (CC 2026) – published in Intelligent Computing, Lecture Notes in Networks and Systems, Springer
Abstract
A study of a hybrid decision support system for industrial plants, based on the integration of Gaussian Process Regression and Bayesian Networks and applied to operational data from a combined-cycle power plant. The approach combines the predictive capability and uncertainty quantification of Gaussian Processes with the interpretable probabilistic reasoning of Bayesian Networks, providing transparent and reliable decision support from an Industry 5.0 perspective.
Authors
M. Proietti, F. Bianchi, L. Sani, A. Vispa, S. Speziali, A. Marini, G. Bartolini, E. Piccioni, A. Garinei, M. Marconi
Link
Publication date: 01/06/2026 Last updated: 02/10/2026 17:21