Dynamic Data-Driven Environmental Systems Science [electronic resource] : First International Conference, DyDESS 2014, Cambridge, MA, USA, November 5-7, 2014, Revised Selected Papers / edited by Sai Ravela, Adrian Sandu.
Contributor(s): Ravela, Sai [editor.] | Sandu, Adrian [editor.] | SpringerLink (Online service).
Material type: BookSeries: Information Systems and Applications, incl. Internet/Web, and HCI: 8964Publisher: Cham : Springer International Publishing : Imprint: Springer, 2015Edition: 1st ed. 2015.Description: XI, 360 p. 145 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319251387.Subject(s): Application software | Algorithms | Computer networks | Artificial intelligence | Software engineering | User interfaces (Computer systems) | Human-computer interaction | Computer and Information Systems Applications | Algorithms | Computer Communication Networks | Artificial Intelligence | Software Engineering | User Interfaces and Human Computer InteractionAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 005.3 Online resources: Click here to access onlineSensing -- Environmental applications -- Reduced representations and features -- data assimilation and uncertainty quantification -- Planning and adaptive observation.
This book constitutes the refereed proceedings of the First International Conference on Dynamic Data-Driven Environmental Systems Science, DyDESS 2014, held in Cambridge, MA, USA, in November 2014. The 24 revised full papers and 7 short papers were carefully reviewed and selected from 62 submissions and cover topics on sensing, imaging and retrieval for the oceans, atmosphere, space, land, earth and planets that is informed by the environmental context; algorithms for modeling and simulation, downscaling, model reduction, data assimilation, uncertainty quantification and statistical learning; methodologies for planning and control, sampling and adaptive observation, and efficient coupling of these algorithms into information-gathering and observing system designs; and applications of methodology to environmental estimation, analysis and prediction including climate, natural hazards, oceans, cryosphere, atmosphere, land, space, earth and planets.
There are no comments for this item.