{"id":"https://openalex.org/W4416535519","doi":"https://doi.org/10.1186/s40537-025-01319-y","title":"Comparative analysis of AI techniques in pavement preservation materials: ensemble learning, deep learning, and simplified variance-matching diffusion model based data augmentation","display_name":"Comparative analysis of AI techniques in pavement preservation materials: ensemble learning, deep learning, and simplified variance-matching diffusion model based data augmentation","publication_year":2025,"publication_date":"2025-11-22","ids":{"openalex":"https://openalex.org/W4416535519","doi":"https://doi.org/10.1186/s40537-025-01319-y"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-025-01319-y","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-025-01319-y","pdf_url":null,"source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1186/s40537-025-01319-y","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042136829","display_name":"Vinay Vakharia","orcid":"https://orcid.org/0000-0001-9791-7525"},"institutions":[{"id":"https://openalex.org/I33586908","display_name":"Pandit Deendayal Energy University","ror":"https://ror.org/02nsv5p42","country_code":"IN","type":"education","lineage":["https://openalex.org/I33586908"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vinay Vakharia","raw_affiliation_strings":["Department of Mechanical Engineering, Pandit Deendayal Energy University, Gandhinagar, 382426, Gujarat, India","Department of Mechanical Engineering, Pandit Deendayal Energy University, Gandhinagar, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Pandit Deendayal Energy University, Gandhinagar, 382426, Gujarat, India","institution_ids":["https://openalex.org/I33586908"]},{"raw_affiliation_string":"Department of Mechanical Engineering, Pandit Deendayal Energy University, Gandhinagar, India","institution_ids":["https://openalex.org/I33586908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085935378","display_name":"Rajesh Gujar","orcid":"https://orcid.org/0000-0001-9199-2524"},"institutions":[{"id":"https://openalex.org/I33586908","display_name":"Pandit Deendayal Energy University","ror":"https://ror.org/02nsv5p42","country_code":"IN","type":"education","lineage":["https://openalex.org/I33586908"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rajesh Gujar","raw_affiliation_strings":["Department of Civil Engineering, Pandit Deendayal Energy University, Gandhinagar, 382426, Gujarat, India","Department of Civil Engineering, Pandit Deendayal Energy University, Gandhinagar, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Pandit Deendayal Energy University, Gandhinagar, 382426, Gujarat, India","institution_ids":["https://openalex.org/I33586908"]},{"raw_affiliation_string":"Department of Civil Engineering, Pandit Deendayal Energy University, Gandhinagar, India","institution_ids":["https://openalex.org/I33586908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032361104","display_name":"Mohd Aamir Mumtaz","orcid":"https://orcid.org/0000-0002-3314-5738"},"institutions":[{"id":"https://openalex.org/I240666556","display_name":"Imam Mohammad ibn Saud Islamic University","ror":"https://ror.org/05gxjyb39","country_code":"SA","type":"education","lineage":["https://openalex.org/I240666556"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Mohd Aamir Mumtaz","raw_affiliation_strings":["Civil Engineering Department, College of Engineering, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia","Civil Engineering Department, College of Engineering, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0002-3314-5738","affiliations":[{"raw_affiliation_string":"Civil Engineering Department, College of Engineering, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia","institution_ids":["https://openalex.org/I240666556"]},{"raw_affiliation_string":"Civil Engineering Department, College of Engineering, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I240666556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044348034","display_name":"Muhammad Imran Khan","orcid":"https://orcid.org/0000-0002-3822-6916"},"institutions":[{"id":"https://openalex.org/I240666556","display_name":"Imam Mohammad ibn Saud Islamic University","ror":"https://ror.org/05gxjyb39","country_code":"SA","type":"education","lineage":["https://openalex.org/I240666556"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Muhammad Imran Khan","raw_affiliation_strings":["Civil Engineering Department, College of Engineering, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia","Civil Engineering Department, College of Engineering, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Civil Engineering Department, College of Engineering, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia","institution_ids":["https://openalex.org/I240666556"]},{"raw_affiliation_string":"Civil Engineering Department, College of Engineering, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I240666556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085074127","display_name":"Hitesh Panchal","orcid":"https://orcid.org/0000-0002-3787-9712"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hitesh Panchal","raw_affiliation_strings":["Department of Mechanical Engineering, Government Engineering College Patan, Patan, Gujarat, India","Department of Mechanical Engineering, Government Engineering College Patan, Patan, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Government Engineering College Patan, Patan, Gujarat, India","institution_ids":[]},{"raw_affiliation_string":"Department of Mechanical Engineering, Government Engineering College Patan, Patan, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059865779","display_name":"Mu\u2019azu Jibrin Musa","orcid":"https://orcid.org/0000-0003-2006-6878"},"institutions":[{"id":"https://openalex.org/I4210143858","display_name":"Maryam Abacha American University of Niger","ror":"https://ror.org/0480gk412","country_code":"NE","type":"education","lineage":["https://openalex.org/I4210143858"]}],"countries":["NE"],"is_corresponding":false,"raw_author_name":"Muazu Jibrin Musa","raw_affiliation_strings":["Department of Computer Engineering, School of Computing, Maryam Abacha American University of Niger, Maradi, Niger"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, School of Computing, Maryam Abacha American University of Niger, Maradi, Niger","institution_ids":["https://openalex.org/I4210143858"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028972122","display_name":"Mohammad Israr","orcid":"https://orcid.org/0000-0002-6770-9570"},"institutions":[{"id":"https://openalex.org/I65734018","display_name":"American University of Nigeria","ror":"https://ror.org/02kv8bx48","country_code":"NG","type":"education","lineage":["https://openalex.org/I65734018"]}],"countries":["NG"],"is_corresponding":false,"raw_author_name":"Mohammad Israr","raw_affiliation_strings":["Maryam Abacha American University of Nigeria, Kano, Nigeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Maryam Abacha American University of Nigeria, Kano, Nigeria","institution_ids":["https://openalex.org/I65734018"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1990,"currency":"USD","value_usd":1990},"apc_paid":{"value":1990,"currency":"USD","value_usd":1990},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27613439,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10264","display_name":"Asphalt Pavement Performance Evaluation","score":0.3303000032901764,"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/T10264","display_name":"Asphalt Pavement Performance Evaluation","score":0.3303000032901764,"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/T10033","display_name":"Concrete and Cement Materials Research","score":0.1817999929189682,"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/T12682","display_name":"Smart Materials for Construction","score":0.17170000076293945,"subfield":{"id":"https://openalex.org/subfields/2310","display_name":"Pollution"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.6865000128746033},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6557000279426575},{"id":"https://openalex.org/keywords/mean-absolute-error","display_name":"Mean absolute error","score":0.61080002784729},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5752000212669373},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5332000255584717},{"id":"https://openalex.org/keywords/mean-absolute-percentage-error","display_name":"Mean absolute percentage error","score":0.5231000185012817},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.46549999713897705},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.45249998569488525},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.4399000108242035},{"id":"https://openalex.org/keywords/approximation-error","display_name":"Approximation error","score":0.39959999918937683}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7272999882698059},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.6865000128746033},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6557000279426575},{"id":"https://openalex.org/C188154048","wikidata":"https://www.wikidata.org/wiki/Q6803609","display_name":"Mean absolute error","level":3,"score":0.61080002784729},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5752000212669373},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5332000255584717},{"id":"https://openalex.org/C150217764","wikidata":"https://www.wikidata.org/wiki/Q6803607","display_name":"Mean absolute percentage error","level":3,"score":0.5231000185012817},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5227000117301941},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5109999775886536},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.46549999713897705},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.45249998569488525},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.4399000108242035},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.39959999918937683},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.399399995803833},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.38850000500679016},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3869999945163727},{"id":"https://openalex.org/C10485038","wikidata":"https://www.wikidata.org/wiki/Q48996162","display_name":"Hyperparameter optimization","level":3,"score":0.36809998750686646},{"id":"https://openalex.org/C24552861","wikidata":"https://www.wikidata.org/wiki/Q2670177","display_name":"Data assimilation","level":2,"score":0.35269999504089355},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.34220001101493835},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3377000093460083},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.3285999894142151},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.30559998750686646},{"id":"https://openalex.org/C68597687","wikidata":"https://www.wikidata.org/wiki/Q362601","display_name":"Computational Science and Engineering","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C203868755","wikidata":"https://www.wikidata.org/wiki/Q5353562","display_name":"Elastic net regularization","level":3,"score":0.28630000352859497},{"id":"https://openalex.org/C5465570","wikidata":"https://www.wikidata.org/wiki/Q5326898","display_name":"Early stopping","level":3,"score":0.2727999985218048},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.2637999951839447},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.26339998841285706},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.25920000672340393},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2533000111579895},{"id":"https://openalex.org/C2779714256","wikidata":"https://www.wikidata.org/wiki/Q25305062","display_name":"Multiple Models","level":2,"score":0.2533000111579895},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s40537-025-01319-y","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-025-01319-y","pdf_url":null,"source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:89a389ab6f0f46ceabf0695558212a41","is_oa":true,"landing_page_url":"https://doaj.org/article/89a389ab6f0f46ceabf0695558212a41","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Big Data, Vol 12, Iss 1, Pp 1-31 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-025-01319-y","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-025-01319-y","pdf_url":null,"source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W2037688578","https://openalex.org/W2057565404","https://openalex.org/W2106843705","https://openalex.org/W2131774270","https://openalex.org/W2561368589","https://openalex.org/W2595740328","https://openalex.org/W2887258823","https://openalex.org/W2895654843","https://openalex.org/W2903014448","https://openalex.org/W2907990558","https://openalex.org/W2919160415","https://openalex.org/W2936891363","https://openalex.org/W2952752408","https://openalex.org/W2962902143","https://openalex.org/W3048971482","https://openalex.org/W3110762250","https://openalex.org/W3177128802","https://openalex.org/W3190878976","https://openalex.org/W4200120247","https://openalex.org/W4281624431","https://openalex.org/W4282563891","https://openalex.org/W4292974997","https://openalex.org/W4308529591","https://openalex.org/W4311379454","https://openalex.org/W4318957115","https://openalex.org/W4320351336","https://openalex.org/W4322739139","https://openalex.org/W4378905741","https://openalex.org/W4383823329","https://openalex.org/W4388494864","https://openalex.org/W4388655813","https://openalex.org/W4390264514","https://openalex.org/W4399641285","https://openalex.org/W4399794553","https://openalex.org/W4400620476","https://openalex.org/W4401889742","https://openalex.org/W4406062673","https://openalex.org/W4406604787","https://openalex.org/W4410345263","https://openalex.org/W4410460980"],"related_works":[],"abstract_inverted_index":{"A":[0],"predictive":[1],"modelling":[2],"framework":[3],"based":[4],"on":[5,42],"machine":[6],"learning":[7,164,168],"(ML)":[8],"was":[9],"created":[10,59],"in":[11,28],"this":[12],"study":[13,46],"to":[14,138],"predict":[15],"the":[16,29,37,45,61,69,133,142],"amounts":[17],"of":[18,31,39],"Fly":[19,23],"ash,":[20,24],"High":[21],"calcium":[22],"and":[25,71,93,110,166],"Hydrated":[26],"lime":[27],"design":[30,188],"pavement":[32,186],"preservation":[33],"materials.":[34],"To":[35],"assess":[36],"effect":[38],"data":[40,50,120],"augmentation":[41],"prediction":[43,76,144,179],"accuracy,":[44],"combined":[47],"actual":[48,118],"experimental":[49,119],"gathered":[51],"from":[52],"laboratory":[53],"experiments":[54],"with":[55,121,129,162],"an":[56],"augmented":[57],"dataset":[58],"using":[60,100],"Simplified":[62],"Variance-Matching":[63],"Diffusion":[64],"Model":[65],"(SVMDM).":[66],"For":[67],"both":[68],"training":[70],"ten-fold":[72],"cross-validation":[73],"(10-CV)":[74],"stages,":[75],"models":[77,165,169],"such":[78],"as":[79],"Extreme":[80],"Gradient":[81],"Boosting":[82],"(XGBoost),":[83],"Recurrent":[84,89],"Neural":[85,90],"Networks":[86,91],"(RNN),":[87],"Bi-":[88],"(Bi-RNN)":[92],"Liquid":[94],"State":[95],"Machine":[96],"(LSM)":[97],"were":[98],"assessed":[99],"Root":[101],"Mean":[102,106,111],"Square":[103],"Error":[104,108,114],"(RMSE)":[105],"Absolute":[107,112],"(MAE)":[109],"Percentage":[113],"(MAPE).":[115],"When":[116],"comparing":[117],"diffusion":[122],"model":[123,127,136,151],"generated":[124],"data,":[125,158],"XGBoost":[126],"optimized":[128],"grid":[130],"search":[131],"demonstrated":[132],"best":[134],"ensemble":[135,163],"adaptability":[137],"supplemented":[139],"datasets,":[140],"maintaining":[141],"lowest":[143],"errors.":[145],"These":[146],"results":[147],"indicate":[148],"that":[149,170],"SVMDM":[150],"is":[152],"a":[153],"useful":[154],"method":[155],"for":[156],"augmenting":[157],"especially":[159],"when":[160],"paired":[161],"deep":[167],"have":[171],"been":[172],"hyperparameter-optimized.":[173],"The":[174],"investigation":[175],"demonstrates":[176],"effective":[177],"material":[178],"techniques":[180],"driven":[181],"by":[182],"AI":[183],"can":[184],"enhance":[185],"materials":[187],"while":[189],"lowering":[190],"experiment":[191],"costs.":[192]},"counts_by_year":[],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-11-23T00:00:00"}
