FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2894776305> ?p ?o ?g. }

• W2894776305 endingPage "1362" @default.
• W2894776305 startingPage "1362" @default.
• W2894776305 abstract "Flood forecasting plays an important role in flood control and water resources management. Recently, the data-driven models with a simpler model structure and lower data requirement attract much more attentions. An extreme learning machine (ELM) method, as a typical data-driven method, with the advantages of a faster learning process and stronger generalization ability, has been taken as an effective tool for flood forecasting. However, an ELM model may suffer from local minima in some cases because of its random generation of input weights and hidden layer biases, which results in uncertainties in the flood forecasting model. Therefore, we proposed an improved ELM model for short-term flood forecasting, in which an emerging dual population-based algorithm, named backtracking search algorithm (BSA), was applied to optimize the parameters of ELM. Thus, the proposed method is called ELM-BSA. The upper Yangtze River was selected as a case study. Several performance indexes were used to evaluate the efficiency of the proposed ELM-BSA model. Then the proposed model was compared with the currently used general regression neural network (GRNN) and ELM models. Results show that the ELM-BSA can always provide better results than the GRNN and ELM models in both the training and testing periods. All these results suggest that the proposed ELM-BSA model is a promising alternative technique for flood forecasting." @default.
• W2894776305 created "2018-10-12" @default.
• W2894776305 creator A5003862827 @default.
• W2894776305 creator A5004263731 @default.
• W2894776305 creator A5009397776 @default.
• W2894776305 creator A5044919859 @default.
• W2894776305 creator A5045890093 @default.
• W2894776305 creator A5066563693 @default.
• W2894776305 creator A5074976831 @default.
• W2894776305 date "2018-09-29" @default.
• W2894776305 modified "2023-10-03" @default.
• W2894776305 title "Flood Forecasting Based on an Improved Extreme Learning Machine Model Combined with the Backtracking Search Optimization Algorithm" @default.
• W2894776305 cites W1567497354 @default.
• W2894776305 cites W1576389639 @default.
• W2894776305 cites W1672654364 @default.
• W2894776305 cites W1673456319 @default.
• W2894776305 cites W1987092188 @default.
• W2894776305 cites W1990561025 @default.
• W2894776305 cites W2004630602 @default.
• W2894776305 cites W2004796972 @default.
• W2894776305 cites W2026471620 @default.
• W2894776305 cites W2033043454 @default.
• W2894776305 cites W2037187959 @default.
• W2894776305 cites W2039801163 @default.
• W2894776305 cites W2046188839 @default.
• W2894776305 cites W2093473119 @default.
• W2894776305 cites W2111072639 @default.
• W2894776305 cites W2139660762 @default.
• W2894776305 cites W2177959459 @default.
• W2894776305 cites W2185358055 @default.
• W2894776305 cites W2255781275 @default.
• W2894776305 cites W2262639697 @default.
• W2894776305 cites W2466177193 @default.
• W2894776305 cites W2473294939 @default.
• W2894776305 cites W2518675717 @default.
• W2894776305 cites W2621795700 @default.
• W2894776305 cites W2739827379 @default.
• W2894776305 cites W2752182860 @default.
• W2894776305 cites W2771024073 @default.
• W2894776305 cites W2779986582 @default.
• W2894776305 cites W2789582427 @default.
• W2894776305 cites W2792616493 @default.
• W2894776305 cites W2799918535 @default.
• W2894776305 cites W2811189390 @default.
• W2894776305 cites W2885582580 @default.
• W2894776305 cites W2888188061 @default.
• W2894776305 cites W2891787868 @default.
• W2894776305 cites W3042541703 @default.
• W2894776305 doi "https://doi.org/10.3390/w10101362" @default.
• W2894776305 hasPublicationYear "2018" @default.
• W2894776305 type Work @default.
• W2894776305 sameAs 2894776305 @default.
• W2894776305 citedByCount "33" @default.
• W2894776305 countsByYear W28947763052018 @default.
• W2894776305 countsByYear W28947763052019 @default.
• W2894776305 countsByYear W28947763052020 @default.
• W2894776305 countsByYear W28947763052021 @default.
• W2894776305 countsByYear W28947763052022 @default.
• W2894776305 countsByYear W28947763052023 @default.
• W2894776305 crossrefType "journal-article" @default.
• W2894776305 hasAuthorship W2894776305A5003862827 @default.
• W2894776305 hasAuthorship W2894776305A5004263731 @default.
• W2894776305 hasAuthorship W2894776305A5009397776 @default.
• W2894776305 hasAuthorship W2894776305A5044919859 @default.
• W2894776305 hasAuthorship W2894776305A5045890093 @default.
• W2894776305 hasAuthorship W2894776305A5066563693 @default.
• W2894776305 hasAuthorship W2894776305A5074976831 @default.
• W2894776305 hasBestOaLocation W28947763051 @default.
• W2894776305 hasConcept C11413529 @default.
• W2894776305 hasConcept C119857082 @default.
• W2894776305 hasConcept C124101348 @default.
• W2894776305 hasConcept C126255220 @default.
• W2894776305 hasConcept C134306372 @default.
• W2894776305 hasConcept C154945302 @default.
• W2894776305 hasConcept C156884757 @default.
• W2894776305 hasConcept C166957645 @default.
• W2894776305 hasConcept C177148314 @default.
• W2894776305 hasConcept C186633575 @default.
• W2894776305 hasConcept C205649164 @default.
• W2894776305 hasConcept C2780150128 @default.
• W2894776305 hasConcept C33923547 @default.
• W2894776305 hasConcept C41008148 @default.
• W2894776305 hasConcept C50644808 @default.
• W2894776305 hasConcept C74256435 @default.
• W2894776305 hasConceptScore W2894776305C11413529 @default.
• W2894776305 hasConceptScore W2894776305C119857082 @default.
• W2894776305 hasConceptScore W2894776305C124101348 @default.
• W2894776305 hasConceptScore W2894776305C126255220 @default.
• W2894776305 hasConceptScore W2894776305C134306372 @default.
• W2894776305 hasConceptScore W2894776305C154945302 @default.
• W2894776305 hasConceptScore W2894776305C156884757 @default.
• W2894776305 hasConceptScore W2894776305C166957645 @default.
• W2894776305 hasConceptScore W2894776305C177148314 @default.
• W2894776305 hasConceptScore W2894776305C186633575 @default.
• W2894776305 hasConceptScore W2894776305C205649164 @default.
• W2894776305 hasConceptScore W2894776305C2780150128 @default.
• W2894776305 hasConceptScore W2894776305C33923547 @default.
• W2894776305 hasConceptScore W2894776305C41008148 @default.

• next