FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2731184913> ?p ?o ?g. }

• W2731184913 endingPage "228" @default.
• W2731184913 startingPage "213" @default.
• W2731184913 abstract "In the present paper, three-dimensional flow fields around single straight groynes with various lengths have been discussed. The dataset of the flow field is measured in the laboratory using Acoustic Doppler Velocimeter (ADV). Then, the longitudinal velocity field is modelled using a novel hybrid method of Genetic Algorithm based artificial neural network (GAA) that has the ability to automatically adjust the number of hidden neurons. To investigate the proposed method’s performance, the results of GAA is measured and compared with one of the most common genetic algorithm based prediction method, namely genetic programming (GP). It is concluded that that GAA model successfully simulates the complex velocity field, and both the velocity magnitudes and isovel shapes are well predicted by this model. The results show that GAA with RMSE of 0.1236 in test data has a significantly better performance than the GP model with RMSE of 0.2342. In addition, it was founded that the transverse coordinate of the measuring point (Y*) is the most important input variable." @default.
• W2731184913 created "2017-07-14" @default.
• W2731184913 creator A5003142398 @default.
• W2731184913 creator A5007701856 @default.
• W2731184913 creator A5086247042 @default.
• W2731184913 date "2017-11-01" @default.
• W2731184913 modified "2023-10-18" @default.
• W2731184913 title "Comparative Assessment of the Hybrid Genetic Algorithm–Artificial Neural Network and Genetic Programming Methods for the Prediction of Longitudinal Velocity Field around a Single Straight Groyne" @default.
• W2731184913 cites W1602486492 @default.
• W2731184913 cites W182956098 @default.
• W2731184913 cites W1967446344 @default.
• W2731184913 cites W1970667047 @default.
• W2731184913 cites W1973504656 @default.
• W2731184913 cites W1974138876 @default.
• W2731184913 cites W1974623009 @default.
• W2731184913 cites W1976019415 @default.
• W2731184913 cites W1979590044 @default.
• W2731184913 cites W1988523040 @default.
• W2731184913 cites W1990786790 @default.
• W2731184913 cites W1991091044 @default.
• W2731184913 cites W1996150433 @default.
• W2731184913 cites W2003091699 @default.
• W2731184913 cites W2012446655 @default.
• W2731184913 cites W2015625984 @default.
• W2731184913 cites W2016764823 @default.
• W2731184913 cites W2018525341 @default.
• W2731184913 cites W2027457810 @default.
• W2731184913 cites W2030272264 @default.
• W2731184913 cites W2030336455 @default.
• W2731184913 cites W2038074227 @default.
• W2731184913 cites W2040132840 @default.
• W2731184913 cites W2041282362 @default.
• W2731184913 cites W2046884547 @default.
• W2731184913 cites W2055351985 @default.
• W2731184913 cites W2072900057 @default.
• W2731184913 cites W2074768444 @default.
• W2731184913 cites W2078484269 @default.
• W2731184913 cites W2078840582 @default.
• W2731184913 cites W2083276746 @default.
• W2731184913 cites W2085291124 @default.
• W2731184913 cites W2085874002 @default.
• W2731184913 cites W2088157920 @default.
• W2731184913 cites W2093818351 @default.
• W2731184913 cites W2094692459 @default.
• W2731184913 cites W2111297239 @default.
• W2731184913 cites W2122722306 @default.
• W2731184913 cites W2128302762 @default.
• W2731184913 cites W2130426385 @default.
• W2731184913 cites W2130908298 @default.
• W2731184913 cites W2131292781 @default.
• W2731184913 cites W2133532129 @default.
• W2731184913 cites W2160715066 @default.
• W2731184913 cites W2162476306 @default.
• W2731184913 cites W2164017619 @default.
• W2731184913 doi "https://doi.org/10.1016/j.asoc.2017.06.048" @default.
• W2731184913 hasPublicationYear "2017" @default.
• W2731184913 type Work @default.
• W2731184913 sameAs 2731184913 @default.
• W2731184913 citedByCount "9" @default.
• W2731184913 countsByYear W27311849132018 @default.
• W2731184913 countsByYear W27311849132019 @default.
• W2731184913 countsByYear W27311849132020 @default.
• W2731184913 countsByYear W27311849132021 @default.
• W2731184913 crossrefType "journal-article" @default.
• W2731184913 hasAuthorship W2731184913A5003142398 @default.
• W2731184913 hasAuthorship W2731184913A5007701856 @default.
• W2731184913 hasAuthorship W2731184913A5086247042 @default.
• W2731184913 hasConcept C105795698 @default.
• W2731184913 hasConcept C110332635 @default.
• W2731184913 hasConcept C11413529 @default.
• W2731184913 hasConcept C119857082 @default.
• W2731184913 hasConcept C139945424 @default.
• W2731184913 hasConcept C154945302 @default.
• W2731184913 hasConcept C16910744 @default.
• W2731184913 hasConcept C199360897 @default.
• W2731184913 hasConcept C202444582 @default.
• W2731184913 hasConcept C2524010 @default.
• W2731184913 hasConcept C28719098 @default.
• W2731184913 hasConcept C33923547 @default.
• W2731184913 hasConcept C38349280 @default.
• W2731184913 hasConcept C41008148 @default.
• W2731184913 hasConcept C50644808 @default.
• W2731184913 hasConcept C8880873 @default.
• W2731184913 hasConcept C9652623 @default.
• W2731184913 hasConceptScore W2731184913C105795698 @default.
• W2731184913 hasConceptScore W2731184913C110332635 @default.
• W2731184913 hasConceptScore W2731184913C11413529 @default.
• W2731184913 hasConceptScore W2731184913C119857082 @default.
• W2731184913 hasConceptScore W2731184913C139945424 @default.
• W2731184913 hasConceptScore W2731184913C154945302 @default.
• W2731184913 hasConceptScore W2731184913C16910744 @default.
• W2731184913 hasConceptScore W2731184913C199360897 @default.
• W2731184913 hasConceptScore W2731184913C202444582 @default.
• W2731184913 hasConceptScore W2731184913C2524010 @default.
• W2731184913 hasConceptScore W2731184913C28719098 @default.
• W2731184913 hasConceptScore W2731184913C33923547 @default.
• W2731184913 hasConceptScore W2731184913C38349280 @default.
• W2731184913 hasConceptScore W2731184913C41008148 @default.

• next