Matches in SemOpenAlex for { <https://semopenalex.org/work/W3106794911> ?p ?o ?g. }
- W3106794911 endingPage "372" @default.
- W3106794911 startingPage "372" @default.
- W3106794911 abstract "Cross-flow microfiltration is a broadly accepted technique for separation of microbial biomass after the cultivation process. However, membrane fouling emerges as the main problem affecting permeate flux decline and separation process efficiency. Hydrodynamic methods, such as turbulence promoters and air sparging, were tested to improve permeate flux during microfiltration. In this study, a non-recurrent feed-forward artificial neural network (ANN) with one hidden layer was examined as a tool for microfiltration modeling using Bacillus velezensis cultivation broth as the feed mixture, while the Kenics static mixer and two-phase flow, as well as their combination, were used to improve permeate flux in microfiltration experiments. The results of this study have confirmed successful application of the ANN model for prediction of permeate flux during microfiltration of Bacillus velezensis cultivation broth with a coefficient of determination of 99.23% and absolute relative error less than 20% for over 95% of the predicted data. The optimal ANN topology was 5-13-1, trained by the Levenberg–Marquardt training algorithm and with hyperbolic sigmoid transfer function between the input and the hidden layer." @default.
- W3106794911 created "2020-12-07" @default.
- W3106794911 creator A5006343265 @default.
- W3106794911 creator A5007130039 @default.
- W3106794911 creator A5024748729 @default.
- W3106794911 creator A5042577833 @default.
- W3106794911 creator A5043148242 @default.
- W3106794911 creator A5071678419 @default.
- W3106794911 creator A5085187239 @default.
- W3106794911 date "2020-11-27" @default.
- W3106794911 modified "2023-09-27" @default.
- W3106794911 title "Dynamic Modeling Using Artificial Neural Network of Bacillus Velezensis Broth Cross-Flow Microfiltration Enhanced by Air-Sparging and Turbulence Promoter" @default.
- W3106794911 cites W1554320534 @default.
- W3106794911 cites W1920126337 @default.
- W3106794911 cites W1965385409 @default.
- W3106794911 cites W1965766173 @default.
- W3106794911 cites W1968428370 @default.
- W3106794911 cites W1968827550 @default.
- W3106794911 cites W1978527143 @default.
- W3106794911 cites W1981797220 @default.
- W3106794911 cites W1987283643 @default.
- W3106794911 cites W1992415618 @default.
- W3106794911 cites W2000128001 @default.
- W3106794911 cites W2001663153 @default.
- W3106794911 cites W2022791667 @default.
- W3106794911 cites W2030497788 @default.
- W3106794911 cites W2045655444 @default.
- W3106794911 cites W2048401737 @default.
- W3106794911 cites W2054958991 @default.
- W3106794911 cites W2055378350 @default.
- W3106794911 cites W2056808208 @default.
- W3106794911 cites W2058599004 @default.
- W3106794911 cites W2058880745 @default.
- W3106794911 cites W2063243391 @default.
- W3106794911 cites W2065161607 @default.
- W3106794911 cites W2067877839 @default.
- W3106794911 cites W2068912744 @default.
- W3106794911 cites W2072880242 @default.
- W3106794911 cites W2078165907 @default.
- W3106794911 cites W2079221207 @default.
- W3106794911 cites W2114135037 @default.
- W3106794911 cites W2469267700 @default.
- W3106794911 cites W2626265518 @default.
- W3106794911 cites W2753743384 @default.
- W3106794911 cites W2801381537 @default.
- W3106794911 cites W2805495711 @default.
- W3106794911 cites W2892704877 @default.
- W3106794911 cites W2897192721 @default.
- W3106794911 cites W2898325002 @default.
- W3106794911 cites W2921298371 @default.
- W3106794911 cites W2944877944 @default.
- W3106794911 cites W2949932717 @default.
- W3106794911 cites W2970752426 @default.
- W3106794911 cites W2971484594 @default.
- W3106794911 cites W2989802124 @default.
- W3106794911 cites W2999400600 @default.
- W3106794911 cites W3002811273 @default.
- W3106794911 cites W3013102575 @default.
- W3106794911 cites W3016088982 @default.
- W3106794911 cites W3081302423 @default.
- W3106794911 cites W3088584218 @default.
- W3106794911 cites W3106424809 @default.
- W3106794911 doi "https://doi.org/10.3390/membranes10120372" @default.
- W3106794911 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7761049" @default.
- W3106794911 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33260842" @default.
- W3106794911 hasPublicationYear "2020" @default.
- W3106794911 type Work @default.
- W3106794911 sameAs 3106794911 @default.
- W3106794911 citedByCount "4" @default.
- W3106794911 countsByYear W31067949112021 @default.
- W3106794911 countsByYear W31067949112022 @default.
- W3106794911 crossrefType "journal-article" @default.
- W3106794911 hasAuthorship W3106794911A5006343265 @default.
- W3106794911 hasAuthorship W3106794911A5007130039 @default.
- W3106794911 hasAuthorship W3106794911A5024748729 @default.
- W3106794911 hasAuthorship W3106794911A5042577833 @default.
- W3106794911 hasAuthorship W3106794911A5043148242 @default.
- W3106794911 hasAuthorship W3106794911A5071678419 @default.
- W3106794911 hasAuthorship W3106794911A5085187239 @default.
- W3106794911 hasBestOaLocation W31067949111 @default.
- W3106794911 hasConcept C100544194 @default.
- W3106794911 hasConcept C112570922 @default.
- W3106794911 hasConcept C115792997 @default.
- W3106794911 hasConcept C121332964 @default.
- W3106794911 hasConcept C154945302 @default.
- W3106794911 hasConcept C180461467 @default.
- W3106794911 hasConcept C185592680 @default.
- W3106794911 hasConcept C18903297 @default.
- W3106794911 hasConcept C192562407 @default.
- W3106794911 hasConcept C196558001 @default.
- W3106794911 hasConcept C2776334353 @default.
- W3106794911 hasConcept C31903555 @default.
- W3106794911 hasConcept C41008148 @default.
- W3106794911 hasConcept C41625074 @default.
- W3106794911 hasConcept C48314217 @default.
- W3106794911 hasConcept C50644808 @default.
- W3106794911 hasConcept C522964758 @default.
- W3106794911 hasConcept C53163501 @default.