TY - GEN
T1 - Probabilistic constraints for nonlinear inverse problems
AU - Carvalho, Elsa
AU - Cruz, Jorge
AU - Barahona, Pedro
PY - 2014
Y1 - 2014
N2 - The probabilistic continuous constraint (PC) framework complements the representation of uncertainty by means of intervals with a probabilistic distribution of values within such intervals. This paper, published in Constraints [8], describes how nonlinear inverse problems can be cast into this framework, highlighting its ability to deal with all the uncertainty aspects of such problems, and illustrates this new methodology in Ocean Color (OC), a research area widely used in climate change studies with significant applications in water quality monitoring.
AB - The probabilistic continuous constraint (PC) framework complements the representation of uncertainty by means of intervals with a probabilistic distribution of values within such intervals. This paper, published in Constraints [8], describes how nonlinear inverse problems can be cast into this framework, highlighting its ability to deal with all the uncertainty aspects of such problems, and illustrates this new methodology in Ocean Color (OC), a research area widely used in climate change studies with significant applications in water quality monitoring.
UR - http://www.scopus.com/inward/record.url?scp=84906266749&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-10428-7_66
DO - 10.1007/978-3-319-10428-7_66
M3 - Conference contribution
AN - SCOPUS:84906266749
SN - 9783319104270
VL - 8656 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 913
EP - 917
BT - Principles and Practice of Constraint Programming - 20th International Conference, CP 2014, Proceedings
PB - Springer Verlag
T2 - 20th International Conference on the Principles and Practice of Constraint Programming, CP 2014
Y2 - 8 September 2014 through 12 September 2014
ER -
