A note on data-driven contaminant simulation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3038, Issue , 2004, Pages 701-708

  Douglas, Craig C ^a,b   Shannon, Chad E ^a   Efendiev, Yalchin ^c   Ewing, Richard ^c   Ginting, Victor ^c   Lazarov, Raytcho ^c   Cole, Martin J ^d   Jones, Greg ^d   Johnson, Chris R ^d   Simpson, Jennifer ^d  

^a UNIVERSITY OF KENTUCKY   (United States)

^b YALE UNIVERSITY   (United States)

^c TEXAS A AND M UNIVERSITY   (United States)

^d UNIVERSITY OF UTAH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SCIENCE; COMPUTERS;

CONTAMINANT SIMULATION; DATA DRIVEN; DYNAMIC-DATA-DRIVEN SIMULATIONS; INTERPOLATION TECHNIQUES; NUMERICAL PROCEDURES; SENSOR DATA; SOLUTION SPACE;

ARTIFICIAL INTELLIGENCE;

EID: 25144493958     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-24688-6_91     Document Type: Article

References (8)

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2. Douglas, G.G., Shannon, C.E., Efendiev, Y., Ewing, R., Lazarov, R., Cole, M.R., Johnson, C.R., Jones, G., Simpson, J.: Virtual telemetry middleware for DDDAS. In Darema, F., ed.: Dynamic Data-Driven Application Systems. Kluwer, Amsterdam (2004)
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7. Lee, S.H., Malallah, A., Datta-Gupta, A., Higdon, D.: Multiscale data integration using markov random fields. SPE Reservoir Evaluation and Engineering (2002)
8. Gilks, W., Richardson, S., Spegelhalter, D.: Markov Cain Monte Carlo in Practice. Chapman and Hall/CRC, London (1996)