Dynamic Data-Driven Environmental Systems Science: First International Conference, DyDESS 2014, Cambridge, MA, USA, November 5-7, 2014, Revised Selected Papers: Lecture Notes in Computer Science, cartea 8964
Editat de Sai Ravela, Adrian Sanduen Limba Engleză Paperback – 27 noi 2015
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.
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Specificații
ISBN-13: 9783319251370
ISBN-10: 3319251376
Pagini: 360
Ilustrații: XI, 360 p. 145 illus. in color.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.52 kg
Ediția:1st ed. 2015
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Information Systems and Applications, incl. Internet/Web, and HCI
Locul publicării:Cham, Switzerland
ISBN-10: 3319251376
Pagini: 360
Ilustrații: XI, 360 p. 145 illus. in color.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.52 kg
Ediția:1st ed. 2015
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Information Systems and Applications, incl. Internet/Web, and HCI
Locul publicării:Cham, Switzerland
Public țintă
ResearchCuprins
Sensing.- Environmental applications.- Reduced representations and features.- data assimilation and uncertainty quantification.- Planning and adaptive observation.
Caracteristici
Includes supplementary material: sn.pub/extras