{"id":"https://openalex.org/W3185625120","doi":"https://doi.org/10.1007/s00521-021-06306-x","title":"Evolving strategies for shear wave velocity estimation: smart and ensemble modeling approach","display_name":"Evolving strategies for shear wave velocity estimation: smart and ensemble modeling approach","publication_year":2021,"publication_date":"2021-07-26","ids":{"openalex":"https://openalex.org/W3185625120","doi":"https://doi.org/10.1007/s00521-021-06306-x","mag":"3185625120"},"language":"en","primary_location":{"id":"doi:10.1007/s00521-021-06306-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00521-021-06306-x","pdf_url":null,"source":{"id":"https://openalex.org/S147897268","display_name":"Neural Computing and Applications","issn_l":"0941-0643","issn":["0941-0643","1433-3058"],"is_oa":false,"is_in_doaj":false,"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-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computing and Applications","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1007/s00521-021-06306-x","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068458892","display_name":"Teslim Olayiwola","orcid":"https://orcid.org/0000-0002-7619-5495"},"institutions":[{"id":"https://openalex.org/I134085113","display_name":"King Fahd University of Petroleum and Minerals","ror":"https://ror.org/03yez3163","country_code":"SA","type":"education","lineage":["https://openalex.org/I134085113"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Teslim Olayiwola","raw_affiliation_strings":["Department of Petroleum Engineering, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia","Department of Petroleum Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Petroleum Engineering, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]},{"raw_affiliation_string":"Department of Petroleum Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081730437","display_name":"Zeeshan Tariq","orcid":"https://orcid.org/0000-0001-5456-7115"},"institutions":[{"id":"https://openalex.org/I134085113","display_name":"King Fahd University of Petroleum and Minerals","ror":"https://ror.org/03yez3163","country_code":"SA","type":"education","lineage":["https://openalex.org/I134085113"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Zeeshan Tariq","raw_affiliation_strings":["Department of Petroleum Engineering, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia","Department of Petroleum Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0001-5456-7115","affiliations":[{"raw_affiliation_string":"Department of Petroleum Engineering, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]},{"raw_affiliation_string":"Department of Petroleum Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053834729","display_name":"Abdulazeez Abdulraheem","orcid":"https://orcid.org/0000-0002-9994-4436"},"institutions":[{"id":"https://openalex.org/I134085113","display_name":"King Fahd University of Petroleum and Minerals","ror":"https://ror.org/03yez3163","country_code":"SA","type":"education","lineage":["https://openalex.org/I134085113"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Abdulazeez Abdulraheem","raw_affiliation_strings":["Department of Petroleum Engineering, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia","Department of Petroleum Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Petroleum Engineering, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]},{"raw_affiliation_string":"Department of Petroleum Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049649985","display_name":"Mohamed Mahmoud","orcid":"https://orcid.org/0000-0002-4395-9567"},"institutions":[{"id":"https://openalex.org/I134085113","display_name":"King Fahd University of Petroleum and Minerals","ror":"https://ror.org/03yez3163","country_code":"SA","type":"education","lineage":["https://openalex.org/I134085113"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Mohamed Mahmoud","raw_affiliation_strings":["Department of Petroleum Engineering, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia","Department of Petroleum Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Petroleum Engineering, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]},{"raw_affiliation_string":"Department of Petroleum Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5049649985","https://openalex.org/A5053834729","https://openalex.org/A5068458892","https://openalex.org/A5081730437"],"corresponding_institution_ids":["https://openalex.org/I134085113"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":2.6061,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.88694412,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"33","issue":"24","first_page":"17147","last_page":"17159"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10892","display_name":"Drilling and Well Engineering","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T10892","display_name":"Drilling and Well Engineering","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11757","display_name":"Seismic Waves and Analysis","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6917359232902527},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6843874454498291},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6571816205978394},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.6523932218551636},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5197851061820984},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5153717398643494},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47881776094436646},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.4475633502006531},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.443559467792511},{"id":"https://openalex.org/keywords/shear","display_name":"Shear (geology)","score":0.41600823402404785},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.41578513383865356},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4102822542190552},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3634037375450134},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.3405383229255676},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.2172929048538208}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6917359232902527},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6843874454498291},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6571816205978394},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.6523932218551636},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5197851061820984},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5153717398643494},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47881776094436646},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.4475633502006531},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.443559467792511},{"id":"https://openalex.org/C96035792","wikidata":"https://www.wikidata.org/wiki/Q43606218","display_name":"Shear (geology)","level":2,"score":0.41600823402404785},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.41578513383865356},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4102822542190552},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3634037375450134},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.3405383229255676},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2172929048538208},{"id":"https://openalex.org/C5900021","wikidata":"https://www.wikidata.org/wiki/Q163082","display_name":"Petrology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s00521-021-06306-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00521-021-06306-x","pdf_url":null,"source":{"id":"https://openalex.org/S147897268","display_name":"Neural Computing and Applications","issn_l":"0941-0643","issn":["0941-0643","1433-3058"],"is_oa":false,"is_in_doaj":false,"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-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computing and Applications","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s00521-021-06306-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s00521-021-06306-x","pdf_url":null,"source":{"id":"https://openalex.org/S147897268","display_name":"Neural Computing and Applications","issn_l":"0941-0643","issn":["0941-0643","1433-3058"],"is_oa":false,"is_in_doaj":false,"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-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computing and Applications","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.6499999761581421}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W596077473","https://openalex.org/W639475909","https://openalex.org/W1534538809","https://openalex.org/W1678356000","https://openalex.org/W1970906652","https://openalex.org/W1975064568","https://openalex.org/W1979795977","https://openalex.org/W1987233112","https://openalex.org/W1988195734","https://openalex.org/W1988790447","https://openalex.org/W2020089616","https://openalex.org/W2025893548","https://openalex.org/W2033591656","https://openalex.org/W2034719372","https://openalex.org/W2041392558","https://openalex.org/W2049081807","https://openalex.org/W2050396801","https://openalex.org/W2062621207","https://openalex.org/W2070493638","https://openalex.org/W2074037274","https://openalex.org/W2078447995","https://openalex.org/W2086760615","https://openalex.org/W2087864878","https://openalex.org/W2092829070","https://openalex.org/W2107098959","https://openalex.org/W2119821739","https://openalex.org/W2129900710","https://openalex.org/W2137226992","https://openalex.org/W2143426320","https://openalex.org/W2147294606","https://openalex.org/W2295598076","https://openalex.org/W2301390796","https://openalex.org/W2344529452","https://openalex.org/W2496233059","https://openalex.org/W2568902225","https://openalex.org/W2578461787","https://openalex.org/W2604427515","https://openalex.org/W2609460191","https://openalex.org/W2766468761","https://openalex.org/W2771379307","https://openalex.org/W2901882553","https://openalex.org/W2911964244","https://openalex.org/W2916048570","https://openalex.org/W2963996045","https://openalex.org/W2994893076","https://openalex.org/W3102476541","https://openalex.org/W4245993775","https://openalex.org/W4247814523"],"related_works":["https://openalex.org/W2967733078","https://openalex.org/W3204430031","https://openalex.org/W3137904399","https://openalex.org/W4310492845","https://openalex.org/W4386690025","https://openalex.org/W2885778889","https://openalex.org/W2766514146","https://openalex.org/W2885516856","https://openalex.org/W4296079469","https://openalex.org/W3208169454"],"abstract_inverted_index":{"Shear":[0],"wave":[1,22],"velocity":[2,23],"has":[3],"many":[4],"applications":[5],"in":[6,24,68,197],"subsurface":[7],"engineering":[8],"such":[9,28,55,143],"as":[10,29,56,144,204],"reservoir":[11],"engineering,":[12],"rock":[13],"mechanics,":[14],"and":[15,32,46,62,84,126,153,180,189,202,210],"seismic":[16],"studies.":[17],"To":[18,49],"estimate":[19],"the":[20,57,69,76,85,108,111,116,130,167,174,177,181],"shear":[21],"rocks,":[25],"different":[26],"methods":[27,54,65,74,195],"laboratory":[30],"experiments":[31],"well":[33,124],"logging":[34],"approaches":[35,39],"are":[36,40,47],"used.":[37],"These":[38],"usually":[41],"involved":[42],"with":[43],"high":[44],"cost":[45],"time-consumption.":[48],"overcome":[50],"these":[51,73],"issues,":[52],"several":[53],"use":[58],"of":[59,72,78,82,87,110,115,122,133,187,191,206],"empirical":[60],"correlations":[61],"machine":[63,140],"learning":[64,141],"were":[66,137,157],"proposed":[67,98],"past.":[70],"Most":[71],"involve":[75],"usage":[77],"a":[79,94],"large":[80],"number":[81,121],"features":[83,179],"formation":[86],"specific":[88],"data":[89,128,132],"points.":[90],"In":[91],"this":[92],"study,":[93],"new":[95],"method":[96],"is":[97],"for":[99],"feature":[100],"selection":[101],"by":[102,184],"coupling":[103],"regression":[104],"algorithms":[105,142],"to":[106,200],"reduce":[107],"likelihood":[109],"error":[112],"introduced":[113],"because":[114],"redundant":[117],"variables.":[118],"A":[119],"substantial":[120],"conventional":[123],"logs":[125],"acoustic":[127],"from":[129],"open-source":[131],"Norwegian":[134],"Volve":[135],"field":[136],"utilized.":[138],"Four":[139],"Random":[145],"forest":[146],"Regressor,":[147],"Adaboosting":[148],"regressor,":[149],"Gradient":[150],"Boosting":[151],"tree,":[152],"Support":[154],"Vector":[155],"Regressor":[156,170],"implemented.":[158],"The":[159,193],"prediction":[160],"results":[161],"on":[162],"testing":[163],"dataset":[164],"showed":[165],"that":[166],"Adaptive":[168],"boosting":[169],"algorithm":[171],"accurately":[172],"predict":[173],"interrelationship":[175],"between":[176,208],"selected":[178],"desired":[182],"output":[183],"yielding":[185],"MAE":[186,198],"0.032":[188],"R2":[190,205],"0.93.":[192],"previous":[194],"resulted":[196],"up":[199],"2.0":[201],"low":[203],"0.5":[207],"actual":[209],"predicted":[211],"values.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":5}],"updated_date":"2026-06-19T17:40:00.097472","created_date":"2025-10-10T00:00:00"}
