{"id":"https://openalex.org/W4312117135","doi":"https://doi.org/10.3390/sym15010033","title":"An Augmented Model of Rutting Data Based on Radial Basis Neural Network","display_name":"An Augmented Model of Rutting Data Based on Radial Basis Neural Network","publication_year":2022,"publication_date":"2022-12-23","ids":{"openalex":"https://openalex.org/W4312117135","doi":"https://doi.org/10.3390/sym15010033"},"language":"en","primary_location":{"id":"doi:10.3390/sym15010033","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym15010033","pdf_url":"https://www.mdpi.com/2073-8994/15/1/33/pdf?version=1671775546","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/15/1/33/pdf?version=1671775546","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037460817","display_name":"Zhuoxuan Li","orcid":"https://orcid.org/0000-0002-2096-6414"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuoxuan Li","raw_affiliation_strings":["Jiangsu Provincial Key Laboratory of Networked Collective Intelligence, Southeast University, Nanjing 210096, China","School of Mathematics, Southeast University, Nanjing 210096, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangsu Provincial Key Laboratory of Networked Collective Intelligence, Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Mathematics, Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101481967","display_name":"Meng Tao","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Tao","raw_affiliation_strings":["Jiangsu Provincial Key Laboratory of Networked Collective Intelligence, Southeast University, Nanjing 210096, China","School of Mathematics, Southeast University, Nanjing 210096, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangsu Provincial Key Laboratory of Networked Collective Intelligence, Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Mathematics, Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017808266","display_name":"Jinde Cao","orcid":"https://orcid.org/0000-0003-3133-7119"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jinde Cao","raw_affiliation_strings":["Jiangsu Provincial Key Laboratory of Networked Collective Intelligence, Southeast University, Nanjing 210096, China","School of Mathematics, Southeast University, Nanjing 210096, China"],"raw_orcid":"https://orcid.org/0000-0003-3133-7119","affiliations":[{"raw_affiliation_string":"Jiangsu Provincial Key Laboratory of Networked Collective Intelligence, Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Mathematics, Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068429082","display_name":"Xinli Shi","orcid":"https://orcid.org/0000-0002-4443-608X"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinli Shi","raw_affiliation_strings":["School of Cyber Science & Engineering, Southeast University, Nanjing 210096, China"],"raw_orcid":"https://orcid.org/0000-0002-4443-608X","affiliations":[{"raw_affiliation_string":"School of Cyber Science & Engineering, Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024545973","display_name":"Tao Ma","orcid":"https://orcid.org/0000-0002-7963-9370"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Ma","raw_affiliation_strings":["School of Transportation, Southeast University, Nanjing 210096, China"],"raw_orcid":"https://orcid.org/0000-0002-7963-9370","affiliations":[{"raw_affiliation_string":"School of Transportation, Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101703876","display_name":"Wei Huang","orcid":"https://orcid.org/0000-0001-7550-1983"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Huang","raw_affiliation_strings":["Intelligent Transportation System Research Center, Southeast University, Nanjing 210096, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Transportation System Research Center, Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5017808266"],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.6916,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.66819173,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"15","issue":"1","first_page":"33","last_page":"33"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9991000294685364,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9991000294685364,"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/T10264","display_name":"Asphalt Pavement Performance Evaluation","score":0.9983999729156494,"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/T14304","display_name":"Transport Systems and Technology","score":0.9412999749183655,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"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/rut","display_name":"Rut","score":0.8970389366149902},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6907626390457153},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.5401029586791992},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5066028833389282},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49032142758369446},{"id":"https://openalex.org/keywords/asphalt","display_name":"Asphalt","score":0.454294353723526},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4282826781272888},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.41449493169784546},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2955717444419861},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2897688150405884},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21157953143119812},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.07869720458984375}],"concepts":[{"id":"https://openalex.org/C76893819","wikidata":"https://www.wikidata.org/wiki/Q596937","display_name":"Rut","level":3,"score":0.8970389366149902},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6907626390457153},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.5401029586791992},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5066028833389282},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49032142758369446},{"id":"https://openalex.org/C168056786","wikidata":"https://www.wikidata.org/wiki/Q202251","display_name":"Asphalt","level":2,"score":0.454294353723526},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4282826781272888},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.41449493169784546},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2955717444419861},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2897688150405884},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21157953143119812},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.07869720458984375},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/sym15010033","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym15010033","pdf_url":"https://www.mdpi.com/2073-8994/15/1/33/pdf?version=1671775546","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3b2dc159f2b4472ab88c7c6a8cc400cd","is_oa":true,"landing_page_url":"https://doaj.org/article/3b2dc159f2b4472ab88c7c6a8cc400cd","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry, Vol 15, Iss 1, p 33 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2073-8994/15/1/33/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/sym15010033","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/sym15010033","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym15010033","pdf_url":"https://www.mdpi.com/2073-8994/15/1/33/pdf?version=1671775546","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.5199999809265137,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4312117135.pdf","grobid_xml":"https://content.openalex.org/works/W4312117135.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W99512890","https://openalex.org/W139359199","https://openalex.org/W144669444","https://openalex.org/W1825825382","https://openalex.org/W1984686364","https://openalex.org/W2041668296","https://openalex.org/W2080547772","https://openalex.org/W2101234009","https://openalex.org/W2122111042","https://openalex.org/W2173443381","https://openalex.org/W2614922859","https://openalex.org/W2886334830","https://openalex.org/W2889131986","https://openalex.org/W2893772597","https://openalex.org/W2969240059","https://openalex.org/W3001478170","https://openalex.org/W3046015915","https://openalex.org/W3080737968","https://openalex.org/W3089808073","https://openalex.org/W3095178014","https://openalex.org/W3095878732","https://openalex.org/W3096454227","https://openalex.org/W3120973688","https://openalex.org/W3144625610","https://openalex.org/W3200808519","https://openalex.org/W3207403499","https://openalex.org/W3209054929","https://openalex.org/W3210570856","https://openalex.org/W4213397551","https://openalex.org/W4220694257","https://openalex.org/W4220976526","https://openalex.org/W4224219891","https://openalex.org/W4226185486","https://openalex.org/W4229035572","https://openalex.org/W4282012251","https://openalex.org/W4283527982","https://openalex.org/W4285740719","https://openalex.org/W4296450803","https://openalex.org/W6604001109","https://openalex.org/W6675354045","https://openalex.org/W6753935598"],"related_works":["https://openalex.org/W3207901993","https://openalex.org/W3026849073","https://openalex.org/W3190066151","https://openalex.org/W2378609698","https://openalex.org/W23618939","https://openalex.org/W3196088517","https://openalex.org/W853136265","https://openalex.org/W2953410182","https://openalex.org/W1975169757","https://openalex.org/W1531525712"],"abstract_inverted_index":{"The":[0],"rutting":[1,19,41,85,144],"depth":[2,20,42,145],"is":[3,44,49,146,166],"an":[4,17,125,134],"important":[5],"index":[6],"to":[7,56],"evaluate":[8],"the":[9,13,29,36,47,66,99,107,114,140,163],"damage":[10],"degree":[11],"of":[12,39,68,103,131,137,143],"pavement.":[14],"Therefore,":[15],"establishing":[16],"accurate":[18],"prediction":[21,59,164],"model":[22,60],"can":[23],"guide":[24],"pavement":[25,33,40,71],"design":[26],"and":[27,46,101,133,150],"provide":[28],"necessary":[30],"basis":[31,93],"for":[32,148,157],"maintenance.":[34],"However,":[35],"sample":[37],"size":[38],"data":[43,67,86,122,142],"small,":[45],"sampling":[48],"not":[50],"standardized,":[51],"which":[52],"makes":[53],"it":[54],"hard":[55],"establish":[57],"a":[58,76],"with":[61,98,124,160],"high":[62],"accuracy.":[63],"Based":[64],"on":[65,90],"RIOHTrack\u2019s":[69],"asphalt":[70,84,104],"structure,":[72],"this":[73,81],"study":[74],"builds":[75],"reliable":[77],"data-augmented":[78],"model.":[79],"In":[80],"paper,":[82],"different":[83],"augmented":[87,141],"models":[88,154],"based":[89],"Gaussian":[91],"radial":[92],"neural":[94,152],"networks":[95],"are":[96,155],"constructed":[97,147],"temperature":[100],"loading":[102],"pavements":[105],"as":[106],"main":[108],"features.":[109],"Experimental":[110],"results":[111],"show":[112],"that":[113],"method":[115],"outperforms":[116],"classical":[117],"machine":[118],"learning":[119],"methods":[120],"in":[121],"augmentation,":[123],"average":[126,135],"root":[127],"mean":[128],"square":[129],"error":[130],"3.95":[132],"R-square":[136],"0.957.":[138],"Finally,":[139],"training,":[149],"multiple":[151],"network":[153],"used":[156],"prediction.":[158],"Compared":[159],"unaugmented":[161],"data,":[162],"accuracy":[165],"increased":[167],"by":[168],"50%.":[169]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
