{"id":"https://openalex.org/W2004288269","doi":"https://doi.org/10.4314/njtr.v8i2.96695","title":"Predicting the Compressive Strength of Concretes Made with Unwashed Gravel from Eastern Nigeria Using Artificial Neural Networks","display_name":"Predicting the Compressive Strength of Concretes Made with Unwashed Gravel from Eastern Nigeria Using Artificial Neural Networks","publication_year":2013,"publication_date":"2013-11-09","ids":{"openalex":"https://openalex.org/W2004288269","doi":"https://doi.org/10.4314/njtr.v8i2.96695","mag":"2004288269"},"language":"en","primary_location":{"id":"doi:10.4314/njtr.v8i2.96695","doi":"https://doi.org/10.4314/njtr.v8i2.96695","is_oa":false,"landing_page_url":"https://doi.org/10.4314/njtr.v8i2.96695","pdf_url":null,"source":{"id":"https://openalex.org/S5406938261","display_name":"Nigerian Journal of Technological Research","issn_l":"0795-5111","issn":["0795-5111"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310321518","host_organization_name":"African Journals OnLine","host_organization_lineage":["https://openalex.org/P4310321518"],"host_organization_lineage_names":["African Journals OnLine"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Nigerian Journal of Technological Research","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053607010","display_name":"Chidozie Chukwuemeka Nwobi-Okoye","orcid":"https://orcid.org/0000-0003-1330-5543","observed_orcids":["https://orcid.org/0000-0003-1330-5543"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chidozie Chukwuemeka Nwobi-Okoye","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5065219387","display_name":"Ikechukwu Etienne Umeonyiagu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ikechukwu Etienne Umeonyiagu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.1709,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.8754823,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"8","issue":"2","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10033","display_name":"Concrete and Cement Materials Research","score":0.29319998621940613,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10033","display_name":"Concrete and Cement Materials Research","score":0.29319998621940613,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10687","display_name":"Innovative concrete reinforcement materials","score":0.26899999380111694,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11847","display_name":"Recycled Aggregate Concrete Performance","score":0.07880000025033951,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/concrete-compressive-strength-prediction","display_name":"concrete compressive strength prediction","score":0.8740000128746033},{"id":"https://openalex.org/keywords/coarse-aggregate","display_name":"coarse aggregate","score":0.7950000166893005},{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":0.8840000033378601},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"multilayer perceptron","score":0.9990000128746033},{"id":"https://openalex.org/keywords/regression-model-comparison","display_name":"regression model comparison","score":0.7509999871253967},{"id":"https://openalex.org/keywords/building-collapse","display_name":"building collapse","score":0.6269999742507935},{"id":"https://openalex.org/keywords/eastern-nigeria","display_name":"Eastern Nigeria","score":0.5550000071525574}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.8364101648330688},{"id":"https://openalex.org/C30407753","wikidata":"https://www.wikidata.org/wiki/Q186191","display_name":"Compressive strength","level":2,"score":0.8013978004455566},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.6902582049369812},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5646077394485474},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5354637503623962},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.49559032917022705},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.47861379384994507},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.47532394528388977},{"id":"https://openalex.org/C149769383","wikidata":"https://www.wikidata.org/wiki/Q7520804","display_name":"Simple linear regression","level":3,"score":0.4705515205860138},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.4361332356929779},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40313494205474854},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.359696626663208},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.35615095496177673},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.346892774105072},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.33248841762542725},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.251552939414978},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23924708366394043},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.21765437722206116},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.10982775688171387},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.4314/njtr.v8i2.96695","doi":"https://doi.org/10.4314/njtr.v8i2.96695","is_oa":false,"landing_page_url":"https://doi.org/10.4314/njtr.v8i2.96695","pdf_url":null,"source":{"id":"https://openalex.org/S5406938261","display_name":"Nigerian Journal of Technological Research","issn_l":"0795-5111","issn":["0795-5111"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310321518","host_organization_name":"African Journals OnLine","host_organization_lineage":["https://openalex.org/P4310321518"],"host_organization_lineage_names":["African Journals OnLine"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Nigerian Journal of Technological Research","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.4943999946117401,"display_name":"Industry, innovation and infrastructure"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W251714914","https://openalex.org/W2219168689","https://openalex.org/W3154055604","https://openalex.org/W3131003044","https://openalex.org/W2901341479","https://openalex.org/W2484846314","https://openalex.org/W2733023736","https://openalex.org/W4401192438","https://openalex.org/W2889355752","https://openalex.org/W6958477538"],"abstract_inverted_index":{"Cases":[0],"of":[1,12,17,26,35,38,68,72,105,139,142,151,162,165,174,208,234],"collapsed":[2],"buildings":[3,43],"and":[4,44,49,144,167,202,215],"structures":[5,45],"are":[6],"prevalent":[7,78],"in":[8,42],"Nigeria.":[9,83],"In":[10],"most":[11],"these":[13],"cases":[14],"the":[15,18,24,27,36,66,69,127,132,154,177,182,189],"cause":[16],"collapse":[19],"could":[20],"be":[21],"traced":[22],"to":[23,55,205],"strength":[25,37,71,103,112,210],"construction":[28],"materials,":[29],"mainly":[30],"concrete.":[31],"Secondly,":[32],"experimental":[33,98,206],"determination":[34,67],"concrete":[39,73,106,131,209],"materials":[40,74],"used":[41],"is":[46,213],"quite":[47],"expensive":[48],"time":[50],"consuming.":[51],"This":[52,192],"research":[53],"seeks":[54],"develop":[56],"a":[57,77,88,137,145,160,168,197],"computational":[58],"model":[59,93,118,134,157,185],"based":[60,119,130,220],"on":[61,120,221],"artificial":[62],"neural":[63,91,155,183],"networks":[64],"for":[65,126],"compressive":[70,102],"made":[75,107],"from":[76,82,101,108],"coarse":[79],"aggregate":[80],"component":[81],"The":[84],"study":[85,193],"involved":[86],"building":[87],"multilayer":[89],"perceptron":[90],"network":[92,156,184],"which":[94],"was":[95],"trained":[96],"using":[97],"data":[99],"obtained":[100],"test":[104],"unwashed":[109,128],"gravel.":[110],"Compressive":[111],"predictions":[113],"were":[114],"compared":[115],"with":[116],"alternative":[117,204],"regression":[121,133,190,222],"analysis.":[122,223],"Results":[123],"show":[124],"that":[125],"gravel":[129],"prediction":[135,158],"has":[136,159,194],"sum":[138,161],"squares":[140,163],"error":[141,150,164,173],"9.808":[143],"mean":[146,169],"absolute":[147,170],"percentage":[148,171],"(relative)":[149,172],"1.167,":[152],"while":[153],"0.025":[166],"0.015.":[175],"Generally,":[176],"models":[178],"predicted":[179,186],"well,":[180],"but":[181],"better":[187],"than":[188,217],"model.":[191],"ably":[195],"demonstrated":[196],"cheap,":[198],"simple,":[199],"very":[200],"quick":[201],"accurate":[203],"method":[207],"determination.":[211],"It":[212],"simpler":[214],"quicker":[216],"analytical":[218],"methods":[219],"Keywords:":[224],"Artificial":[225],"Neural":[226],"Network,":[227],"Concrete,":[228],"Unwashed":[229],"gravel,":[230],"Regression,":[231],"ModellingNigerian":[232],"Journal":[233],"Technological":[235],"Research,":[236],"18(2),":[237],"2013":[238]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2026-08-13T07:04:57.449891","created_date":"2016-06-24T00:00:00"}