{"id":"https://openalex.org/W7128314187","doi":"https://doi.org/10.5281/zenodo.18528489","title":"Synthetic Dataset for Non-Linear Rock Mass Rating (RMR) Prediction using Machine Learning","display_name":"Synthetic Dataset for Non-Linear Rock Mass Rating (RMR) Prediction using Machine Learning","publication_year":2026,"publication_date":"2026-02-09","ids":{"openalex":"https://openalex.org/W7128314187","doi":"https://doi.org/10.5281/zenodo.18528489"},"language":"en","primary_location":{"id":"doi:10.5281/zenodo.18528489","doi":"https://doi.org/10.5281/zenodo.18528489","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.18528489","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"volume":null,"type":"dataset","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.5281/zenodo.18528489","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119619145","display_name":"Ertugrul Karakaplan","orcid":"https://orcid.org/0000-0003-0142-3171","observed_orcids":["https://orcid.org/0000-0003-0142-3171"]},"institutions":[{"id":"https://openalex.org/I48843708","display_name":"Pamukkale University","ror":"https://ror.org/01etz1309","country_code":"TR","type":"education","lineage":["https://openalex.org/I48843708"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"KARAKAPLAN, ERTU\u011eRUL","raw_affiliation_strings":["Pamukkale University"],"raw_orcid":"https://orcid.org/0000-0003-0142-3171","affiliations":[{"raw_affiliation_string":"Pamukkale University","institution_ids":["https://openalex.org/I48843708"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5119619145"],"corresponding_institution_ids":["https://openalex.org/I48843708"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10161","display_name":"Rock Mechanics and Modeling","score":0.8676999807357788,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/T10161","display_name":"Rock Mechanics and Modeling","score":0.8676999807357788,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/T12482","display_name":"Tunneling and Rock Mechanics","score":0.1193000003695488,"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/T11046","display_name":"Geotechnical Engineering and Analysis","score":0.006000000052154064,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/rock-mass-rating","display_name":"rock mass rating","score":0.9620000123977661},{"id":"https://openalex.org/keywords/monte-carlo-simulation","display_name":"Monte Carlo simulation","score":0.890999972820282},{"id":"https://openalex.org/keywords/groundwater-impacts","display_name":"groundwater influence","score":0.5709999799728394},{"id":"https://openalex.org/keywords/discontinuity-conditions","display_name":"discontinuity conditions","score":0.7820000052452087},{"id":"https://openalex.org/keywords/uniaxial-compressive-strength","display_name":"uniaxial compressive strength","score":0.9419999718666077},{"id":"https://openalex.org/keywords/rock-quality-designation","display_name":"rock quality designation","score":0.9200000166893005},{"id":"https://openalex.org/keywords/discontinuity-spacing","display_name":"discontinuity spacing","score":0.9160000085830688},{"id":"https://openalex.org/keywords/nonlinear-relationship","display_name":"nonlinear relationship","score":0.5830000042915344},{"id":"https://openalex.org/keywords/rock-mass-characterization","display_name":"rock mass characterization","score":0.42899999022483826}],"concepts":[{"id":"https://openalex.org/C41242791","wikidata":"https://www.wikidata.org/wiki/Q17105549","display_name":"Rock mass classification","level":2,"score":0.7986000180244446},{"id":"https://openalex.org/C95918197","wikidata":"https://www.wikidata.org/wiki/Q1133006","display_name":"Rock mass rating","level":3,"score":0.7814000248908997},{"id":"https://openalex.org/C2777042112","wikidata":"https://www.wikidata.org/wiki/Q5281658","display_name":"Discontinuity (linguistics)","level":2,"score":0.6796000003814697},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.6480000019073486},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48890000581741333},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4494999945163727},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43529999256134033},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43369999527931213},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4235000014305115},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.4223000109195709},{"id":"https://openalex.org/C72490741","wikidata":"https://www.wikidata.org/wiki/Q5535315","display_name":"Geological Strength Index","level":3,"score":0.3849000036716461},{"id":"https://openalex.org/C97842125","wikidata":"https://www.wikidata.org/wiki/Q1191291","display_name":"Rock mechanics","level":2,"score":0.3783000111579895},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3779999911785126},{"id":"https://openalex.org/C76177295","wikidata":"https://www.wikidata.org/wiki/Q161598","display_name":"Groundwater","level":2,"score":0.3758000135421753},{"id":"https://openalex.org/C75622301","wikidata":"https://www.wikidata.org/wiki/Q208791","display_name":"Aquifer","level":3,"score":0.3612000048160553},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.3361999988555908},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.301800012588501},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2892000079154968},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2777000069618225},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27070000767707825},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.25769999623298645}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.5281/zenodo.18528489","doi":"https://doi.org/10.5281/zenodo.18528489","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.18528489","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Dataset"},{"id":"doi:10.5281/zenodo.18528490","doi":"https://doi.org/10.5281/zenodo.18528490","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.18528490","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Dataset"},{"id":"doi:10.5281/zenodo.18704885","doi":"https://doi.org/10.5281/zenodo.18704885","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.18704885","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Dataset"}],"best_oa_location":{"id":"doi:10.5281/zenodo.18528489","doi":"https://doi.org/10.5281/zenodo.18528489","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.18528489","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dataset"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0,154],"dataset":[1,27,63,155],"contains":[2],"2000":[3],"samples":[4],"of":[5,43,79,128],"synthetic":[6],"rock":[7],"mass":[8],"parameters":[9],"generated":[10,62],"via":[11],"Monte":[12],"Carlo":[13],"simulation":[14],"to":[15,30,56,71,150],"test":[16],"machine":[17],"learning":[18],"models":[19],"for":[20,142],"Rock":[21,91,163],"Mass":[22,164],"Rating":[23,165],"(RMR)":[24,166],"prediction.":[25],"The":[26,58,119,133],"was":[28],"designed":[29],"simulate":[31],"non-linear":[32,139],"interactions":[33,144],"found":[34],"in":[35,162],"geological":[36],"environments,":[37],"specifically":[38],"the":[39,61,66,80,129,157],"combined":[40],"negative":[41],"effect":[42],"groundwater":[44],"and":[45,65,77,145],"poor":[46],"discontinuity":[47],"conditions,":[48],"which":[49],"traditional":[50],"linear":[51],"RMR":[52,121],"summation":[53,127],"methods":[54],"fail":[55],"capture.":[57],"repository":[59],"includes":[60],"(.csv)":[64],"Python":[67],"scripts":[68],"(.py)":[69],"used":[70],"generate":[72],"it,":[73],"ensuring":[74],"full":[75],"transparency":[76],"reproducibility":[78],"methodology.":[81],"Variables":[82],"(Columns):":[83],"UCS_MPa:":[84],"Uniaxial":[85],"Compressive":[86],"Strength":[87],"(5-250":[88],"MPa).":[89],"RQD_Percent:":[90],"Quality":[92],"Designation":[93],"(10-100%).":[94],"Spacing_mm:":[95],"Discontinuity":[96,101],"Spacing":[97],"(20-4000":[98],"mm).":[99],"Condition_Score:":[100],"Condition":[102],"based":[103],"on":[104],"Bieniawski":[105],"(1989)":[106],"(0-30":[107],"points).":[108,117],"Groundwater_Score:":[109],"Groundwater":[110],"conditions":[111],"(0,":[112],"4,":[113],"7,":[114],"10,":[115],"15":[116],"Calculated_Classic_RMR:":[118],"theoretical":[120],"value":[122],"calculated":[123],"by":[124],"simple":[125],"arithmetic":[126],"five":[130],"parameters.":[131],"Target_RMR_Field:":[132],"simulated":[134],"\"Ground":[135],"Truth\"":[136],"value,":[137],"incorporating":[138],"penalty":[140],"functions":[141],"water-clay":[143],"Gaussian":[146],"noise":[147],"(mean=0,":[148],"std=5)":[149],"represent":[151],"field":[152],"uncertainties.":[153],"supports":[156],"study:":[158],"\"Modeling":[159],"Non-Linear":[160],"Relationships":[161],"System:":[167],"A":[168],"Methodological":[169],"Stacking-Based":[170],"Hybrid":[171],"Approach\".":[172]},"counts_by_year":[],"updated_date":"2026-10-08T09:06:37.294493","created_date":"2026-02-09T00:00:00"}