FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W1965295747> ?p ?o ?g. }

• W1965295747 endingPage "223" @default.
• W1965295747 startingPage "223" @default.
• W1965295747 abstract "In the recent past, machine learning (ML) techniques such as artificial neural networks (ANN) have been increasingly used to model algal bloom dynamics. In the present paper, along with ANN, we select genetic programming (GP) for modelling and prediction of algal blooms in Tolo Harbour, Hong Kong. The study of the weights of the trained ANN and also the GP-evolved equations shows that they correctly identify the ecologically significant variables. Analysis of various ANN and GP scenarios indicates that good predictions of long-term trends in algal biomass can be obtained using only chlorophyll-a as input. The results indicate that the use of biweekly data can simulate long-term trends of algal biomass reasonably well, but it is not ideally suited to give short-term algal bloom predictions." @default.
• W1965295747 created "2016-06-24" @default.
• W1965295747 creator A5034626947 @default.
• W1965295747 creator A5081904302 @default.
• W1965295747 date "2006-01-01" @default.
• W1965295747 modified "2023-09-24" @default.
• W1965295747 title "Neural network and genetic programming for modelling coastal algal blooms" @default.
• W1965295747 cites W1479763026 @default.
• W1965295747 cites W1490210040 @default.
• W1965295747 cites W1504082289 @default.
• W1965295747 cites W1510730483 @default.
• W1965295747 cites W1529146523 @default.
• W1965295747 cites W1705128246 @default.
• W1965295747 cites W1965313284 @default.
• W1965295747 cites W1965433882 @default.
• W1965295747 cites W1972956867 @default.
• W1965295747 cites W1983183860 @default.
• W1965295747 cites W1996846790 @default.
• W1965295747 cites W1998442441 @default.
• W1965295747 cites W2018287529 @default.
• W1965295747 cites W2027735689 @default.
• W1965295747 cites W2031085925 @default.
• W1965295747 cites W2036916277 @default.
• W1965295747 cites W2037556099 @default.
• W1965295747 cites W2039252893 @default.
• W1965295747 cites W2045002121 @default.
• W1965295747 cites W2067565268 @default.
• W1965295747 cites W2081335822 @default.
• W1965295747 cites W2095115170 @default.
• W1965295747 cites W2100604298 @default.
• W1965295747 cites W2119310493 @default.
• W1965295747 cites W2124776405 @default.
• W1965295747 cites W2125372574 @default.
• W1965295747 cites W2126005761 @default.
• W1965295747 cites W2129972123 @default.
• W1965295747 cites W2138467337 @default.
• W1965295747 cites W2142845953 @default.
• W1965295747 cites W2245772228 @default.
• W1965295747 cites W3023540311 @default.
• W1965295747 doi "https://doi.org/10.1504/ijep.2006.011208" @default.
• W1965295747 hasPublicationYear "2006" @default.
• W1965295747 type Work @default.
• W1965295747 sameAs 1965295747 @default.
• W1965295747 citedByCount "315" @default.
• W1965295747 countsByYear W19652957472012 @default.
• W1965295747 countsByYear W19652957472013 @default.
• W1965295747 countsByYear W19652957472014 @default.
• W1965295747 countsByYear W19652957472015 @default.
• W1965295747 countsByYear W19652957472016 @default.
• W1965295747 countsByYear W19652957472017 @default.
• W1965295747 countsByYear W19652957472018 @default.
• W1965295747 countsByYear W19652957472019 @default.
• W1965295747 countsByYear W19652957472020 @default.
• W1965295747 countsByYear W19652957472021 @default.
• W1965295747 countsByYear W19652957472022 @default.
• W1965295747 countsByYear W19652957472023 @default.
• W1965295747 crossrefType "journal-article" @default.
• W1965295747 hasAuthorship W1965295747A5034626947 @default.
• W1965295747 hasAuthorship W1965295747A5081904302 @default.
• W1965295747 hasBestOaLocation W19652957472 @default.
• W1965295747 hasConcept C110332635 @default.
• W1965295747 hasConcept C111368507 @default.
• W1965295747 hasConcept C120305227 @default.
• W1965295747 hasConcept C127313418 @default.
• W1965295747 hasConcept C142796444 @default.
• W1965295747 hasConcept C154945302 @default.
• W1965295747 hasConcept C18903297 @default.
• W1965295747 hasConcept C2780892065 @default.
• W1965295747 hasConcept C39432304 @default.
• W1965295747 hasConcept C41008148 @default.
• W1965295747 hasConcept C50644808 @default.
• W1965295747 hasConcept C86803240 @default.
• W1965295747 hasConceptScore W1965295747C110332635 @default.
• W1965295747 hasConceptScore W1965295747C111368507 @default.
• W1965295747 hasConceptScore W1965295747C120305227 @default.
• W1965295747 hasConceptScore W1965295747C127313418 @default.
• W1965295747 hasConceptScore W1965295747C142796444 @default.
• W1965295747 hasConceptScore W1965295747C154945302 @default.
• W1965295747 hasConceptScore W1965295747C18903297 @default.
• W1965295747 hasConceptScore W1965295747C2780892065 @default.
• W1965295747 hasConceptScore W1965295747C39432304 @default.
• W1965295747 hasConceptScore W1965295747C41008148 @default.
• W1965295747 hasConceptScore W1965295747C50644808 @default.
• W1965295747 hasConceptScore W1965295747C86803240 @default.
• W1965295747 hasIssue "3/4" @default.
• W1965295747 hasLocation W19652957471 @default.
• W1965295747 hasLocation W19652957472 @default.
• W1965295747 hasOpenAccess W1965295747 @default.
• W1965295747 hasPrimaryLocation W19652957471 @default.
• W1965295747 hasRelatedWork W2003799049 @default.
• W1965295747 hasRelatedWork W2004012112 @default.
• W1965295747 hasRelatedWork W2119420728 @default.
• W1965295747 hasRelatedWork W2386387936 @default.
• W1965295747 hasRelatedWork W2808782363 @default.
• W1965295747 hasRelatedWork W2899084033 @default.
• W1965295747 hasRelatedWork W3014447972 @default.
• W1965295747 hasRelatedWork W4285114792 @default.
• W1965295747 hasRelatedWork W4287827086 @default.

• next