FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2060037118> ?p ?o ?g. }

• W2060037118 endingPage "113" @default.
• W2060037118 startingPage "102" @default.
• W2060037118 abstract "Reservoir operating rules are often derived using either a fitting or a simulation-based optimization method in the context of implicit stochastic optimization. Analysis of the parameter uncertainty in reservoir operating rules and their impact is necessary for robust solutions. In the present study, parameter uncertainty for reservoir operating rules is analyzed using two statistical methods, linear regression (LR) and Bayesian simulation (BS). LR estimates the confidence interval based on fitting the operating rules to the optimal deterministic solution. BS deals with the operating rule parameters as stochastic variables and treats the goodness-of-fit to the optimal deterministic solution or the operation profits as the likelihood measure. Two alternative techniques, the generalized likelihood uncertainty estimation (GLUE) and Markov Chain Monte Carlo method (MCMC), are implemented for the BS uncertainty analysis. These methods were applied to the operating rules of China’s Three Gorges Reservoir. The LR performed less than the BS, and the MCMC outperformed the GLUE. Even for the BS methods, the operation profits criterion was better than the goodness-of-fit criterion for deriving the reservoir operating rules." @default.
• W2060037118 created "2016-06-24" @default.
• W2060037118 creator A5025602649 @default.
• W2060037118 creator A5038259858 @default.
• W2060037118 creator A5070436377 @default.
• W2060037118 creator A5081853271 @default.
• W2060037118 date "2014-06-01" @default.
• W2060037118 modified "2023-10-12" @default.
• W2060037118 title "Parameter uncertainty analysis of reservoir operating rules based on implicit stochastic optimization" @default.
• W2060037118 cites W1490048247 @default.
• W2060037118 cites W1499556847 @default.
• W2060037118 cites W1507764682 @default.
• W2060037118 cites W1544278534 @default.
• W2060037118 cites W1594703822 @default.
• W2060037118 cites W1628093780 @default.
• W2060037118 cites W1644023502 @default.
• W2060037118 cites W1679242182 @default.
• W2060037118 cites W1803359428 @default.
• W2060037118 cites W1863721346 @default.
• W2060037118 cites W1909649765 @default.
• W2060037118 cites W1942934012 @default.
• W2060037118 cites W1952079638 @default.
• W2060037118 cites W1974452437 @default.
• W2060037118 cites W1986703162 @default.
• W2060037118 cites W1991921673 @default.
• W2060037118 cites W1995780830 @default.
• W2060037118 cites W2010432367 @default.
• W2060037118 cites W2013858742 @default.
• W2060037118 cites W2014017508 @default.
• W2060037118 cites W2028740558 @default.
• W2060037118 cites W2028788069 @default.
• W2060037118 cites W2029591667 @default.
• W2060037118 cites W2034417616 @default.
• W2060037118 cites W2034456430 @default.
• W2060037118 cites W2040329770 @default.
• W2060037118 cites W2045133470 @default.
• W2060037118 cites W2056063759 @default.
• W2060037118 cites W2069002482 @default.
• W2060037118 cites W2078890104 @default.
• W2060037118 cites W2079976398 @default.
• W2060037118 cites W2086252391 @default.
• W2060037118 cites W2089958590 @default.
• W2060037118 cites W2093233187 @default.
• W2060037118 cites W2099329408 @default.
• W2060037118 cites W2101472376 @default.
• W2060037118 cites W2117319840 @default.
• W2060037118 cites W2120347659 @default.
• W2060037118 cites W2124738823 @default.
• W2060037118 cites W2136558239 @default.
• W2060037118 cites W2139660762 @default.
• W2060037118 cites W2146495904 @default.
• W2060037118 cites W2154938752 @default.
• W2060037118 cites W2155001774 @default.
• W2060037118 cites W2155633525 @default.
• W2060037118 cites W2158582237 @default.
• W2060037118 cites W2159830737 @default.
• W2060037118 cites W2160472521 @default.
• W2060037118 cites W2169039305 @default.
• W2060037118 cites W2169476226 @default.
• W2060037118 cites W2344815732 @default.
• W2060037118 doi "https://doi.org/10.1016/j.jhydrol.2014.04.012" @default.
• W2060037118 hasPublicationYear "2014" @default.
• W2060037118 type Work @default.
• W2060037118 sameAs 2060037118 @default.
• W2060037118 citedByCount "83" @default.
• W2060037118 countsByYear W20600371182015 @default.
• W2060037118 countsByYear W20600371182016 @default.
• W2060037118 countsByYear W20600371182017 @default.
• W2060037118 countsByYear W20600371182018 @default.
• W2060037118 countsByYear W20600371182019 @default.
• W2060037118 countsByYear W20600371182020 @default.
• W2060037118 countsByYear W20600371182021 @default.
• W2060037118 countsByYear W20600371182022 @default.
• W2060037118 countsByYear W20600371182023 @default.
• W2060037118 crossrefType "journal-article" @default.
• W2060037118 hasAuthorship W2060037118A5025602649 @default.
• W2060037118 hasAuthorship W2060037118A5038259858 @default.
• W2060037118 hasAuthorship W2060037118A5070436377 @default.
• W2060037118 hasAuthorship W2060037118A5081853271 @default.
• W2060037118 hasConcept C105795698 @default.
• W2060037118 hasConcept C107673813 @default.
• W2060037118 hasConcept C111350023 @default.
• W2060037118 hasConcept C114614502 @default.
• W2060037118 hasConcept C126255220 @default.
• W2060037118 hasConcept C127413603 @default.
• W2060037118 hasConcept C151730666 @default.
• W2060037118 hasConcept C177803969 @default.
• W2060037118 hasConcept C2778067643 @default.
• W2060037118 hasConcept C2779343474 @default.
• W2060037118 hasConcept C2779937294 @default.
• W2060037118 hasConcept C33923547 @default.
• W2060037118 hasConcept C41008148 @default.
• W2060037118 hasConcept C44154836 @default.
• W2060037118 hasConcept C78519656 @default.
• W2060037118 hasConcept C86803240 @default.
• W2060037118 hasConceptScore W2060037118C105795698 @default.
• W2060037118 hasConceptScore W2060037118C107673813 @default.
• W2060037118 hasConceptScore W2060037118C111350023 @default.

• next