FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4289315676> ?p ?o ?g. }

• W4289315676 endingPage "26" @default.
• W4289315676 startingPage "1" @default.
• W4289315676 abstract "Most building structures that are built today are built from concrete, owing to its various favorable properties. Compressive strength is one of the mechanical properties of concrete that is directly related to the safety of the structures. Therefore, predicting the compressive strength can facilitate the early planning of material quality management. A series of deep learning (DL) models that suit computer vision tasks, namely the convolutional neural networks (CNNs), are used to predict the compressive strength of ready-mixed concrete. To demonstrate the efficacy of computer vision-based prediction, its effectiveness using imaging numerical data was compared with that of the deep neural networks (DNNs) technique that uses conventional numerical data. Various DL prediction models were compared and the best ones were identified with the relevant concrete datasets. The best DL models were then optimized by fine-tuning their hyperparameters using a newly developed bio-inspired metaheuristic algorithm, called jellyfish search optimizer, to enhance the accuracy and reliability. Analytical experiments indicate that the computer vision-based CNNs outperform the numerical data-based DNNs in all evaluation metrics except the training time. Thus, the bio-inspired optimization of computer vision-based convolutional neural networks is potentially a promising approach to predict the compressive strength of ready-mixed concrete." @default.
• W4289315676 created "2022-08-02" @default.
• W4289315676 creator A5018906851 @default.
• W4289315676 creator A5043651248 @default.
• W4289315676 creator A5072837427 @default.
• W4289315676 date "2022-08-01" @default.
• W4289315676 modified "2023-10-18" @default.
• W4289315676 title "Jellyfish Search-Optimized Deep Learning for Compressive Strength Prediction in Images of Ready-Mixed Concrete" @default.
• W4289315676 cites W1970245951 @default.
• W4289315676 cites W1999284878 @default.
• W4289315676 cites W2052321038 @default.
• W4289315676 cites W2073404525 @default.
• W4289315676 cites W2075858332 @default.
• W4289315676 cites W2076063813 @default.
• W4289315676 cites W2087641133 @default.
• W4289315676 cites W2124972241 @default.
• W4289315676 cites W2149192839 @default.
• W4289315676 cites W2152195021 @default.
• W4289315676 cites W2183341477 @default.
• W4289315676 cites W2194775991 @default.
• W4289315676 cites W2302255633 @default.
• W4289315676 cites W2531409750 @default.
• W4289315676 cites W2594760301 @default.
• W4289315676 cites W2621888941 @default.
• W4289315676 cites W2651534614 @default.
• W4289315676 cites W2800017313 @default.
• W4289315676 cites W2801822775 @default.
• W4289315676 cites W2804860796 @default.
• W4289315676 cites W2902067542 @default.
• W4289315676 cites W2963163009 @default.
• W4289315676 cites W2963446712 @default.
• W4289315676 cites W2964081807 @default.
• W4289315676 cites W2964938350 @default.
• W4289315676 cites W2980292896 @default.
• W4289315676 cites W2997748707 @default.
• W4289315676 cites W3022139725 @default.
• W4289315676 cites W3023935218 @default.
• W4289315676 cites W3036260130 @default.
• W4289315676 cites W3043160233 @default.
• W4289315676 cites W3048311949 @default.
• W4289315676 cites W3087036690 @default.
• W4289315676 cites W3104499636 @default.
• W4289315676 cites W3122662561 @default.
• W4289315676 cites W3132653939 @default.
• W4289315676 cites W3137653757 @default.
• W4289315676 cites W3171750385 @default.
• W4289315676 cites W3197695332 @default.
• W4289315676 cites W4205646372 @default.
• W4289315676 cites W4206548443 @default.
• W4289315676 cites W4210504877 @default.
• W4289315676 cites W4210740993 @default.
• W4289315676 cites W4250503569 @default.
• W4289315676 cites W4297775537 @default.
• W4289315676 cites W4300939921 @default.
• W4289315676 cites W4320930577 @default.
• W4289315676 doi "https://doi.org/10.1155/2022/9541115" @default.
• W4289315676 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35958762" @default.
• W4289315676 hasPublicationYear "2022" @default.
• W4289315676 type Work @default.
• W4289315676 citedByCount "4" @default.
• W4289315676 countsByYear W42893156762022 @default.
• W4289315676 countsByYear W42893156762023 @default.
• W4289315676 crossrefType "journal-article" @default.
• W4289315676 hasAuthorship W4289315676A5018906851 @default.
• W4289315676 hasAuthorship W4289315676A5043651248 @default.
• W4289315676 hasAuthorship W4289315676A5072837427 @default.
• W4289315676 hasBestOaLocation W42893156761 @default.
• W4289315676 hasConcept C108583219 @default.
• W4289315676 hasConcept C119857082 @default.
• W4289315676 hasConcept C121332964 @default.
• W4289315676 hasConcept C124101348 @default.
• W4289315676 hasConcept C124851039 @default.
• W4289315676 hasConcept C153180895 @default.
• W4289315676 hasConcept C154945302 @default.
• W4289315676 hasConcept C159985019 @default.
• W4289315676 hasConcept C163258240 @default.
• W4289315676 hasConcept C192562407 @default.
• W4289315676 hasConcept C30407753 @default.
• W4289315676 hasConcept C41008148 @default.
• W4289315676 hasConcept C43214815 @default.
• W4289315676 hasConcept C50644808 @default.
• W4289315676 hasConcept C62520636 @default.
• W4289315676 hasConcept C81363708 @default.
• W4289315676 hasConcept C8642999 @default.
• W4289315676 hasConceptScore W4289315676C108583219 @default.
• W4289315676 hasConceptScore W4289315676C119857082 @default.
• W4289315676 hasConceptScore W4289315676C121332964 @default.
• W4289315676 hasConceptScore W4289315676C124101348 @default.
• W4289315676 hasConceptScore W4289315676C124851039 @default.
• W4289315676 hasConceptScore W4289315676C153180895 @default.
• W4289315676 hasConceptScore W4289315676C154945302 @default.
• W4289315676 hasConceptScore W4289315676C159985019 @default.
• W4289315676 hasConceptScore W4289315676C163258240 @default.
• W4289315676 hasConceptScore W4289315676C192562407 @default.
• W4289315676 hasConceptScore W4289315676C30407753 @default.
• W4289315676 hasConceptScore W4289315676C41008148 @default.
• W4289315676 hasConceptScore W4289315676C43214815 @default.
• W4289315676 hasConceptScore W4289315676C50644808 @default.

• next