Matches in SemOpenAlex for { <https://semopenalex.org/work/W2904896091> ?p ?o ?g. }
Showing items 1 to 94 of
94
with 100 items per page.
- W2904896091 endingPage "59" @default.
- W2904896091 startingPage "50" @default.
- W2904896091 abstract "As dissolved oxygen (DO) is an important indicator of water quality in aquaculture, an accurate prediction for DO can effectively improve quantity and quality of product. Accordingly, a novel hybrid dissolved oxygen prediction model, which combines the multiple-factor analysis and the multi-scale feature extraction, is proposed. Firstly, considering that dissolved oxygen is affected by complex factors, water temperature and pH are chosen as the most relevant environmental factors for dissolved oxygen, using grey relational degree method. Secondly, the ensemble empirical mode decomposition (EEMD) is adopted to decompose the dissolved oxygen, water temperature and pH data into several sub-sequences, respectively. Then, the sample entropy (SE) algorithm reconstructs the sub-sequences to obtain the trend component, random component and detail component. Lastly, regularized extreme learning machine (RELM), a currently effective and stable artificial intelligent (AI) tool, is applied to predict three components independently. The prediction models of random component, detail component and trend component are RELM1, RELM2 and RELM3 respectively. The dissolved oxygen, water temperature and pH of the random component forms the input layer of RELM1, and predicted value of dissolved oxygen in the random component is the output layer of RELM1. The input and output of RELM2 and RELM3 are similar to that of RELM1. Final prediction results are obtained by superimposing three components predicted values. One of the main features of the proposed approach is that it integrates the multiple-factor analysis and the multi-scale feature extraction using grey correlation analysis and EEMD. Its performance is compared with several outstanding algorithms. Results for experiment show that the proposed model has satisfactory performance and high precision." @default.
- W2904896091 created "2018-12-22" @default.
- W2904896091 creator A5003360183 @default.
- W2904896091 creator A5008990100 @default.
- W2904896091 creator A5016983875 @default.
- W2904896091 creator A5042559726 @default.
- W2904896091 creator A5089682040 @default.
- W2904896091 date "2019-02-01" @default.
- W2904896091 modified "2023-10-16" @default.
- W2904896091 title "A combined model of dissolved oxygen prediction in the pond based on multiple-factor analysis and multi-scale feature extraction" @default.
- W2904896091 cites W1977784344 @default.
- W2904896091 cites W1985505861 @default.
- W2904896091 cites W2022173539 @default.
- W2904896091 cites W2075153278 @default.
- W2904896091 cites W2123066915 @default.
- W2904896091 cites W2156567404 @default.
- W2904896091 cites W2175385431 @default.
- W2904896091 cites W2286725013 @default.
- W2904896091 cites W2565982626 @default.
- W2904896091 cites W2593400527 @default.
- W2904896091 cites W2753260324 @default.
- W2904896091 cites W2787918399 @default.
- W2904896091 cites W2791460302 @default.
- W2904896091 cites W2791937529 @default.
- W2904896091 cites W2792747764 @default.
- W2904896091 cites W2801998166 @default.
- W2904896091 cites W2802952027 @default.
- W2904896091 doi "https://doi.org/10.1016/j.aquaeng.2018.12.003" @default.
- W2904896091 hasPublicationYear "2019" @default.
- W2904896091 type Work @default.
- W2904896091 sameAs 2904896091 @default.
- W2904896091 citedByCount "26" @default.
- W2904896091 countsByYear W29048960912019 @default.
- W2904896091 countsByYear W29048960912020 @default.
- W2904896091 countsByYear W29048960912021 @default.
- W2904896091 countsByYear W29048960912022 @default.
- W2904896091 countsByYear W29048960912023 @default.
- W2904896091 crossrefType "journal-article" @default.
- W2904896091 hasAuthorship W2904896091A5003360183 @default.
- W2904896091 hasAuthorship W2904896091A5008990100 @default.
- W2904896091 hasAuthorship W2904896091A5016983875 @default.
- W2904896091 hasAuthorship W2904896091A5042559726 @default.
- W2904896091 hasAuthorship W2904896091A5089682040 @default.
- W2904896091 hasConcept C121332964 @default.
- W2904896091 hasConcept C124101348 @default.
- W2904896091 hasConcept C154945302 @default.
- W2904896091 hasConcept C168167062 @default.
- W2904896091 hasConcept C169258074 @default.
- W2904896091 hasConcept C186060115 @default.
- W2904896091 hasConcept C18903297 @default.
- W2904896091 hasConcept C27438332 @default.
- W2904896091 hasConcept C2778755073 @default.
- W2904896091 hasConcept C2780797713 @default.
- W2904896091 hasConcept C41008148 @default.
- W2904896091 hasConcept C52622490 @default.
- W2904896091 hasConcept C62520636 @default.
- W2904896091 hasConcept C86803240 @default.
- W2904896091 hasConcept C97355855 @default.
- W2904896091 hasConceptScore W2904896091C121332964 @default.
- W2904896091 hasConceptScore W2904896091C124101348 @default.
- W2904896091 hasConceptScore W2904896091C154945302 @default.
- W2904896091 hasConceptScore W2904896091C168167062 @default.
- W2904896091 hasConceptScore W2904896091C169258074 @default.
- W2904896091 hasConceptScore W2904896091C186060115 @default.
- W2904896091 hasConceptScore W2904896091C18903297 @default.
- W2904896091 hasConceptScore W2904896091C27438332 @default.
- W2904896091 hasConceptScore W2904896091C2778755073 @default.
- W2904896091 hasConceptScore W2904896091C2780797713 @default.
- W2904896091 hasConceptScore W2904896091C41008148 @default.
- W2904896091 hasConceptScore W2904896091C52622490 @default.
- W2904896091 hasConceptScore W2904896091C62520636 @default.
- W2904896091 hasConceptScore W2904896091C86803240 @default.
- W2904896091 hasConceptScore W2904896091C97355855 @default.
- W2904896091 hasFunder F4320321001 @default.
- W2904896091 hasLocation W29048960911 @default.
- W2904896091 hasOpenAccess W2904896091 @default.
- W2904896091 hasPrimaryLocation W29048960911 @default.
- W2904896091 hasRelatedWork W1771356744 @default.
- W2904896091 hasRelatedWork W2060518359 @default.
- W2904896091 hasRelatedWork W2085553065 @default.
- W2904896091 hasRelatedWork W2114966906 @default.
- W2904896091 hasRelatedWork W2132729794 @default.
- W2904896091 hasRelatedWork W2147478239 @default.
- W2904896091 hasRelatedWork W2189511392 @default.
- W2904896091 hasRelatedWork W2352079147 @default.
- W2904896091 hasRelatedWork W2352842738 @default.
- W2904896091 hasRelatedWork W2353697322 @default.
- W2904896091 hasVolume "84" @default.
- W2904896091 isParatext "false" @default.
- W2904896091 isRetracted "false" @default.
- W2904896091 magId "2904896091" @default.
- W2904896091 workType "article" @default.