TY - GEN
T1 - High dimensional stochastic simulation and electric ship models
AU - Taylor, Josh
AU - Hover, Franz
PY - 2007
Y1 - 2007
N2 - Determination of statistical moments requires the numerical computation of integrals, but as the number of random dimensions increases, computational cost grows dramatically. There is great interest in the large scale complex systems encountered in the all-electric ship, and to deal with the large dimension, we present the sparse grid technique based on Smolyak's algorithm for evaluating mid-dimensional integrals. We compare its performance with collocation (full grid) and Monte Carlo methods, first focusing on a now standard package of six test integrals proposed by Genz. We then apply these methods to a validated electric ship model to compute mean and variance behaviors, given variation in physical parameters, both individually and in ranked sets.
AB - Determination of statistical moments requires the numerical computation of integrals, but as the number of random dimensions increases, computational cost grows dramatically. There is great interest in the large scale complex systems encountered in the all-electric ship, and to deal with the large dimension, we present the sparse grid technique based on Smolyak's algorithm for evaluating mid-dimensional integrals. We compare its performance with collocation (full grid) and Monte Carlo methods, first focusing on a now standard package of six test integrals proposed by Genz. We then apply these methods to a validated electric ship model to compute mean and variance behaviors, given variation in physical parameters, both individually and in ranked sets.
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U2 - 10.1109/ESTS.2007.372117
DO - 10.1109/ESTS.2007.372117
M3 - Conference contribution
AN - SCOPUS:34548814979
SN - 1424409470
SN - 9781424409471
T3 - IEEE Electric Ship Technologies Symposium, ESTS 2007
SP - 402
EP - 407
BT - IEEE Electric Ship Technologies Symposium, ESTS 2007
T2 - IEEE Electric Ship Technologies Symposium, ESTS 2007
Y2 - 21 May 2007 through 23 May 2007
ER -