YongjieLi,Ka InHoi,Kai MengMok,Ka VengYuen
Air Quality Monitoring and Advanced Bayesian Modeling
Air Quality Monitoring and Advanced Bayesian Modeling
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Excellent- More about Air Quality Monitoring and Advanced Bayesian Modeling
Air Quality Monitoring and Advanced Bayesian Modeling is a book that discusses recent developments in urban air quality monitoring and forecasting. It covers monitoring methods, advanced characterization techniques, and emerging strategies, and illustrates concepts through case studies. Readers will learn advanced topics such as Bayesian model class selection, adaptive forecasting, and averaging of multiple models.
Format: Paperback / softback
Length: 322 pages
Publication date: 17 January 2023
Publisher: Elsevier - Health Sciences Division
Air Quality Monitoring and Advanced Bayesian Modeling delves into the latest advancements in urban air quality monitoring and forecasting. This comprehensive book offers a comprehensive exploration of concepts, theories, and case studies related to monitoring methods for criteria air pollutants, advanced techniques for real-time characterization of chemical composition of PM and VOCs, and emerging strategies for air quality monitoring. Through illustrative case studies, the book elucidates key concepts and theories, showcasing their practical applications in developing common statistical air quality forecasting models. Additionally, readers will gain valuable insights into advanced topics such as Bayesian model class selection, adaptive forecasting model development with Kalman filters, and the Bayesian model averaging of multiple adaptive forecasting models. This resource is an invaluable tool for professionals, researchers, and policymakers seeking to stay informed about the latest developments in air quality management and forecasting.
Air Quality Monitoring and Advanced Bayesian Modeling presents the latest developments in urban air quality monitoring and forecasting. This comprehensive book offers a comprehensive exploration of concepts, theories, and case studies related to monitoring methods for criteria air pollutants, advanced techniques for real-time characterization of chemical composition of PM and VOCs, and emerging strategies for air quality monitoring.
Through illustrative case studies, the book elucidates key concepts and theories, showcasing their practical applications in developing common statistical air quality forecasting models. Additionally, readers will gain valuable insights into advanced topics such as Bayesian model class selection, adaptive forecasting model development with Kalman filters, and the Bayesian model averaging of multiple adaptive forecasting models.
This resource is an invaluable tool for professionals, researchers, and policymakers seeking to stay informed about the latest developments in air quality management and forecasting.
Weight: 668g
Dimension: 232 x 192 x 19 (mm)
ISBN-13: 9780323902663
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