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{"key"=>"Campanile2024558", "type"=>"Conference paper", "bibtex"=>"@conference{Campanile2024558,\n author = {Campanile, Lelio and Di Bonito, Luigi Piero and Natale, Francesco Di and Iacono, Mauro},\n title = {Ensemble Models for Predicting CO Concentrations: Application and Explainability in Environmental Monitoring in Campania, Italy},\n year = {2024},\n journal = {Proceedings - European Council for Modelling and Simulation, ECMS},\n volume = {38},\n number = {1},\n pages = {558 – 564},\n doi = {10.7148/2024-0558}\n}\n", "author"=>"Campanile, Lelio and Di Bonito, Luigi Piero and Natale, Francesco Di and Iacono, Mauro", "author_array"=>[{"first"=>"Lelio", "last"=>"Campanile", "prefix"=>"", "suffix"=>""}, {"first"=>"Luigi Piero", "last"=>"Di Bonito", "prefix"=>"", "suffix"=>""}, {"first"=>"Francesco Di", "last"=>"Natale", "prefix"=>"", "suffix"=>""}, {"first"=>"Mauro", "last"=>"Iacono", "prefix"=>"", "suffix"=>""}], "author_0_first"=>"Lelio", "author_0_last"=>"Campanile", "author_0_prefix"=>"", "author_0_suffix"=>"", "author_1_first"=>"Luigi Piero", "author_1_last"=>"Di Bonito", "author_1_prefix"=>"", "author_1_suffix"=>"", "author_2_first"=>"Francesco Di", "author_2_last"=>"Natale", "author_2_prefix"=>"", "author_2_suffix"=>"", "author_3_first"=>"Mauro", "author_3_last"=>"Iacono", "author_3_prefix"=>"", "author_3_suffix"=>"", "title"=>"Ensemble Models for Predicting CO Concentrations: Application and Explainability in Environmental Monitoring in Campania, Italy", "year"=>"2024", "journal"=>"Proceedings - European Council for Modelling and Simulation, ECMS", "volume"=>"38", "number"=>"1", "pages"=>"558 – 564", "doi"=>"10.7148/2024-0558", "url"=>"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195192701&doi=10.7148%2f2024-0558&partnerID=40&md5=0f267aa7e7f451217cd093496cef39c5", "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. © ECMS Daniel Grzonka, Natalia Rylko, Grazyna Suchacka, Vladimir Mityushev (Editors) 2024.", "author_keywords"=>"Carbon monoxide; Environmental Monitoring; eX-plainalble Artificial Intelligence; Machine Learning; Pollution", "keywords"=>"Learning systems; Machine learning; Campania; CO concentrations; Ensemble models; Environmental conditions; Environmental Monitoring; Ex-plainalble artificial intelligence; Informed decision; Machine-learning; Non-linear phenomenon; Pollution dynamics; Carbon monoxide", "publication_stage"=>"Final", "source"=>"Scopus", "note"=>"Cited by: 2"}