Matches in SemOpenAlex for { <https://semopenalex.org/work/W2892881687> ?p ?o ?g. }
Showing items 1 to 85 of
85
with 100 items per page.
- W2892881687 abstract "Evaporation duct is a particular atmospheric layer that is crucial for marine vessel communication. Evaporation duct height (EDH) is a vital index to measure evaporation duct architecture and intensity. The most common method to calculate EDH is model diagnosis, and the most prevalent model is Paulus-J eseke (P-J) model. This paper raises a new method to optimize the P-J model based on multilayer perceptron (MLP), a typical neural network in deep learning. To assess the performance of this method, some observation experiment data-sets are introduced here, which were conducted in some sea areas during March 2013 to May 2013. Root-mean-squared error (RMSE) is used as the evaluation index, and comparison between MLP P-J and classic P-J model indicates that the estimation precision of EDH based on this method is significantly higher than that of classic P-J model over all observation experiment areas, which implies that this method with deep learning is a better approach for evaporation duct diagnose model research." @default.
- W2892881687 created "2018-10-05" @default.
- W2892881687 creator A5017533636 @default.
- W2892881687 creator A5022639310 @default.
- W2892881687 creator A5050314106 @default.
- W2892881687 creator A5076949809 @default.
- W2892881687 creator A5089684709 @default.
- W2892881687 date "2018-05-01" @default.
- W2892881687 modified "2023-10-18" @default.
- W2892881687 title "An Optimization Research of Evaporation Duct Prediction Models Based on a Deep Learning Method" @default.
- W2892881687 cites W1518561662 @default.
- W2892881687 cites W1977237085 @default.
- W2892881687 cites W1991816149 @default.
- W2892881687 cites W2067557309 @default.
- W2892881687 cites W2072595677 @default.
- W2892881687 cites W2077901559 @default.
- W2892881687 cites W2103496339 @default.
- W2892881687 cites W2120178384 @default.
- W2892881687 cites W2137983211 @default.
- W2892881687 cites W2146725832 @default.
- W2892881687 cites W2527915846 @default.
- W2892881687 cites W4244872196 @default.
- W2892881687 doi "https://doi.org/10.1109/imcec.2018.8469552" @default.
- W2892881687 hasPublicationYear "2018" @default.
- W2892881687 type Work @default.
- W2892881687 sameAs 2892881687 @default.
- W2892881687 citedByCount "4" @default.
- W2892881687 countsByYear W28928816872019 @default.
- W2892881687 countsByYear W28928816872020 @default.
- W2892881687 countsByYear W28928816872023 @default.
- W2892881687 crossrefType "proceedings-article" @default.
- W2892881687 hasAuthorship W2892881687A5017533636 @default.
- W2892881687 hasAuthorship W2892881687A5022639310 @default.
- W2892881687 hasAuthorship W2892881687A5050314106 @default.
- W2892881687 hasAuthorship W2892881687A5076949809 @default.
- W2892881687 hasAuthorship W2892881687A5089684709 @default.
- W2892881687 hasConcept C105795698 @default.
- W2892881687 hasConcept C108583219 @default.
- W2892881687 hasConcept C119857082 @default.
- W2892881687 hasConcept C121332964 @default.
- W2892881687 hasConcept C139945424 @default.
- W2892881687 hasConcept C142724271 @default.
- W2892881687 hasConcept C153294291 @default.
- W2892881687 hasConcept C154945302 @default.
- W2892881687 hasConcept C179717631 @default.
- W2892881687 hasConcept C2781212128 @default.
- W2892881687 hasConcept C33923547 @default.
- W2892881687 hasConcept C41008148 @default.
- W2892881687 hasConcept C50644808 @default.
- W2892881687 hasConcept C60908668 @default.
- W2892881687 hasConcept C61441594 @default.
- W2892881687 hasConcept C71924100 @default.
- W2892881687 hasConceptScore W2892881687C105795698 @default.
- W2892881687 hasConceptScore W2892881687C108583219 @default.
- W2892881687 hasConceptScore W2892881687C119857082 @default.
- W2892881687 hasConceptScore W2892881687C121332964 @default.
- W2892881687 hasConceptScore W2892881687C139945424 @default.
- W2892881687 hasConceptScore W2892881687C142724271 @default.
- W2892881687 hasConceptScore W2892881687C153294291 @default.
- W2892881687 hasConceptScore W2892881687C154945302 @default.
- W2892881687 hasConceptScore W2892881687C179717631 @default.
- W2892881687 hasConceptScore W2892881687C2781212128 @default.
- W2892881687 hasConceptScore W2892881687C33923547 @default.
- W2892881687 hasConceptScore W2892881687C41008148 @default.
- W2892881687 hasConceptScore W2892881687C50644808 @default.
- W2892881687 hasConceptScore W2892881687C60908668 @default.
- W2892881687 hasConceptScore W2892881687C61441594 @default.
- W2892881687 hasConceptScore W2892881687C71924100 @default.
- W2892881687 hasLocation W28928816871 @default.
- W2892881687 hasOpenAccess W2892881687 @default.
- W2892881687 hasPrimaryLocation W28928816871 @default.
- W2892881687 hasRelatedWork W1501213224 @default.
- W2892881687 hasRelatedWork W2091943352 @default.
- W2892881687 hasRelatedWork W2749461815 @default.
- W2892881687 hasRelatedWork W2890929759 @default.
- W2892881687 hasRelatedWork W3185179407 @default.
- W2892881687 hasRelatedWork W3211546796 @default.
- W2892881687 hasRelatedWork W4226023263 @default.
- W2892881687 hasRelatedWork W4231994957 @default.
- W2892881687 hasRelatedWork W4322750901 @default.
- W2892881687 hasRelatedWork W4381616756 @default.
- W2892881687 isParatext "false" @default.
- W2892881687 isRetracted "false" @default.
- W2892881687 magId "2892881687" @default.
- W2892881687 workType "article" @default.