Monitoring of non-linear phenomena, such as pollution dynamics, which is the result of several combined factors and the evolution of environmental conditions, greatly benefits by AI tools; a larger benefit derives by the application of explainable solutions, which are capable of providing elements to understand those dynamics for better informed decisions. In this paper we discuss a case with real data in which a posteriori explanations have been produced after the application of ensemble models.
Ensemble Models for Predicting CO Concentrations: Application and Explainability in Environmental Monitoring in Campania, Italy
Campanile L.
;Di Bonito L. P.
;Iacono M.
2024
Abstract
Monitoring of non-linear phenomena, such as pollution dynamics, which is the result of several combined factors and the evolution of environmental conditions, greatly benefits by AI tools; a larger benefit derives by the application of explainable solutions, which are capable of providing elements to understand those dynamics for better informed decisions. In this paper we discuss a case with real data in which a posteriori explanations have been produced after the application of ensemble models.File in questo prodotto:
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