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dc.contributor.authorStefano Mazzoleni*
dc.contributor.authorChristian E. Vincenot*
dc.contributor.authorLael Parrott*
dc.date.accessioned2021-02-11T15:40:51Z
dc.date.available2021-02-11T15:40:51Z
dc.date.issued2017*
dc.date.submitted2017-07-06 13:27:36*
dc.identifier22908*
dc.identifier.issn16648714*
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/49704
dc.description.abstractSystems studied in environmental science, due to their structure and the heterogeneity of the entities composing them, often exhibit complex dynamics that can only be captured by hybrid modeling approaches. While several concurrent definitions of “hybrid modeling” can be found in the literature, it is defined here broadly as the approach consisting in coupling existing modelling paradigms to achieve a more accurate or efficient representation of systems. The need for hybrid models generally arises from the necessity to overcome the limitation of a single modeling technique in terms of structural flexibility, capabilities, or computational efficiency. This book brings together experts in the field of hybrid modelling to demonstrate how this approach can address the challenge of representing the complexity of natural systems. Chapters cover applied examples as well as modeling methodology.Systems studied in environmental science, due to their structure and the heterogeneity of the entities composing them, often exhibit complex dynamics that can only be captured by hybrid modeling approaches. While several concurrent definitions of “hybrid modeling” can be found in the literature, it is defined here broadly as the approach consisting in coupling existing modelling paradigms to achieve a more accurate or efficient representation of systems. The need for hybrid models generally arises from the necessity to overcome the limitation of a single modeling technique in terms of structural flexibility, capabilities, or computational efficiency. This book brings together experts in the field of hybrid modelling to demonstrate how this approach can address the challenge of representing the complexity of natural systems. Chapters cover applied examples as well as modeling methodology.*
dc.languageEnglish*
dc.relation.ispartofseriesFrontiers Research Topics*
dc.subjectGE1-350*
dc.subjectQ1-390*
dc.subject.classificationthema EDItEUR::K Economics, Finance, Business and Management::KC Economics::KCV Economics of specific sectors::KCVG Environmental economicsen_US
dc.subject.othersystem dynamics*
dc.subject.otherMultiscale integration*
dc.subject.othersimulation*
dc.subject.otherMixed model*
dc.subject.otherhierarchical structure*
dc.subject.otherCombined approach*
dc.subject.othermachine learning*
dc.subject.otheragent-based modelling*
dc.subject.otherparadigm shift*
dc.subject.othernetwork*
dc.titleHybrid Solutions for the Modelling of Complex Environmental Systems*
dc.typebook
oapen.identifier.doi10.3389/978-2-88945-055-8*
oapen.relation.isPublishedBybf5ce210-e72e-4860-ba9b-c305640ff3ae*
oapen.relation.isbn9782889450558*
oapen.pages184*


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