Matches in SemOpenAlex for { <https://semopenalex.org/work/W2942547243> ?p ?o ?g. }
Showing items 1 to 93 of
93
with 100 items per page.
- W2942547243 abstract "We investigate Monte Carlo based algorithms for solving stochastic control problems with probabilistic constraints. Our motivation comes from microgrid management, where the controller tries to optimally dispatch a diesel generator while maintaining low probability of blackouts. The key question we investigate are empirical simulation procedures for learning the admissible control set that is specified implicitly through a probability constraint on the system state. We propose a variety of relevant statistical tools including logistic regression, Gaussian process regression, quantile regression and support vector machines, which we then incorporate into an overall Regression Monte Carlo (RMC) framework for approximate dynamic programming. Our results indicate that using logistic or Gaussian process regression to estimate the admissibility probability outperforms the other options. Our algorithms offer an efficient and reliable extension of RMC to probability-constrained control. We illustrate our findings with two case studies for the microgrid problem." @default.
- W2942547243 created "2019-05-09" @default.
- W2942547243 creator A5034730622 @default.
- W2942547243 creator A5061522790 @default.
- W2942547243 creator A5061741185 @default.
- W2942547243 creator A5074760129 @default.
- W2942547243 date "2019-04-30" @default.
- W2942547243 modified "2023-09-23" @default.
- W2942547243 title "Statistical Learning for Probability-Constrained Stochastic Optimal Control" @default.
- W2942547243 cites W1144593952 @default.
- W2942547243 cites W1551775352 @default.
- W2942547243 cites W1655517863 @default.
- W2942547243 cites W1993486129 @default.
- W2942547243 cites W1999131722 @default.
- W2942547243 cites W2011621283 @default.
- W2942547243 cites W2071316111 @default.
- W2942547243 cites W2072321868 @default.
- W2942547243 cites W2096999004 @default.
- W2942547243 cites W2097148013 @default.
- W2942547243 cites W2099506495 @default.
- W2942547243 cites W2126311658 @default.
- W2942547243 cites W2142453884 @default.
- W2942547243 cites W2143514150 @default.
- W2942547243 cites W2152565894 @default.
- W2942547243 cites W2154032554 @default.
- W2942547243 cites W2167412190 @default.
- W2942547243 cites W2177430769 @default.
- W2942547243 cites W2229105208 @default.
- W2942547243 cites W2254756147 @default.
- W2942547243 cites W2279173213 @default.
- W2942547243 cites W2328704064 @default.
- W2942547243 cites W2406551241 @default.
- W2942547243 cites W2441957133 @default.
- W2942547243 cites W2605897681 @default.
- W2942547243 cites W2608659566 @default.
- W2942547243 cites W2769395101 @default.
- W2942547243 cites W2780924880 @default.
- W2942547243 cites W2963046861 @default.
- W2942547243 cites W3048727147 @default.
- W2942547243 cites W3123753597 @default.
- W2942547243 cites W65048577 @default.
- W2942547243 cites W73692560 @default.
- W2942547243 cites W88909337 @default.
- W2942547243 hasPublicationYear "2019" @default.
- W2942547243 type Work @default.
- W2942547243 sameAs 2942547243 @default.
- W2942547243 citedByCount "0" @default.
- W2942547243 crossrefType "posted-content" @default.
- W2942547243 hasAuthorship W2942547243A5034730622 @default.
- W2942547243 hasAuthorship W2942547243A5061522790 @default.
- W2942547243 hasAuthorship W2942547243A5061741185 @default.
- W2942547243 hasAuthorship W2942547243A5074760129 @default.
- W2942547243 hasConcept C105795698 @default.
- W2942547243 hasConcept C126255220 @default.
- W2942547243 hasConcept C154945302 @default.
- W2942547243 hasConcept C19499675 @default.
- W2942547243 hasConcept C33923547 @default.
- W2942547243 hasConcept C41008148 @default.
- W2942547243 hasConcept C49937458 @default.
- W2942547243 hasConceptScore W2942547243C105795698 @default.
- W2942547243 hasConceptScore W2942547243C126255220 @default.
- W2942547243 hasConceptScore W2942547243C154945302 @default.
- W2942547243 hasConceptScore W2942547243C19499675 @default.
- W2942547243 hasConceptScore W2942547243C33923547 @default.
- W2942547243 hasConceptScore W2942547243C41008148 @default.
- W2942547243 hasConceptScore W2942547243C49937458 @default.
- W2942547243 hasLocation W29425472431 @default.
- W2942547243 hasOpenAccess W2942547243 @default.
- W2942547243 hasPrimaryLocation W29425472431 @default.
- W2942547243 hasRelatedWork W1506745328 @default.
- W2942547243 hasRelatedWork W1996289149 @default.
- W2942547243 hasRelatedWork W2010684217 @default.
- W2942547243 hasRelatedWork W2042584453 @default.
- W2942547243 hasRelatedWork W2051159254 @default.
- W2942547243 hasRelatedWork W2148932877 @default.
- W2942547243 hasRelatedWork W2150124787 @default.
- W2942547243 hasRelatedWork W2155550114 @default.
- W2942547243 hasRelatedWork W2157240767 @default.
- W2942547243 hasRelatedWork W2322459871 @default.
- W2942547243 hasRelatedWork W2626999623 @default.
- W2942547243 hasRelatedWork W2796036893 @default.
- W2942547243 hasRelatedWork W293147621 @default.
- W2942547243 hasRelatedWork W2954405902 @default.
- W2942547243 hasRelatedWork W2963015832 @default.
- W2942547243 hasRelatedWork W2990745812 @default.
- W2942547243 hasRelatedWork W3135219656 @default.
- W2942547243 hasRelatedWork W3172697571 @default.
- W2942547243 hasRelatedWork W3200282560 @default.
- W2942547243 hasRelatedWork W2132408602 @default.
- W2942547243 isParatext "false" @default.
- W2942547243 isRetracted "false" @default.
- W2942547243 magId "2942547243" @default.
- W2942547243 workType "article" @default.