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Conference Paper: Comparison of different Kernel-based Probabilistic Models and Regression Methods in retrieving Ground-Level NO2 Concentrations over Southern China based upon Satellite Remote Sensing datasets

TitleComparison of different Kernel-based Probabilistic Models and Regression Methods in retrieving Ground-Level NO2 Concentrations over Southern China based upon Satellite Remote Sensing datasets
Authors
Mak, HWLFung, JC
Issue Date2018
Citation
Big Data Challenges for Predictive Modeling of Complex Systems, Hong Kong, 26-30 November 2018 How to Cite?
Persistent Identifierhttp://hdl.handle.net/10722/283086

 

DC FieldValueLanguage
dc.contributor.authorMak, HWL-
dc.contributor.authorFung, JC-
dc.date.accessioned2020-06-09T07:07:25Z-
dc.date.available2020-06-09T07:07:25Z-
dc.date.issued2018-
dc.identifier.citationBig Data Challenges for Predictive Modeling of Complex Systems, Hong Kong, 26-30 November 2018-
dc.identifier.urihttp://hdl.handle.net/10722/283086-
dc.languageeng-
dc.relation.ispartofBig Data Challenges for Predictive Modeling of Complex Systems-
dc.titleComparison of different Kernel-based Probabilistic Models and Regression Methods in retrieving Ground-Level NO2 Concentrations over Southern China based upon Satellite Remote Sensing datasets-
dc.typeConference_Paper-
dc.identifier.emailMak, HWL: hwlmak@hku.hk-
dc.identifier.authorityMak, HWL=rp02674-
dc.publisher.placeHong Kong-

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