{"id":"https://openalex.org/W3003738623","doi":"https://doi.org/10.1017/s0890060420000025","title":"Developing a new hybrid soft computing technique in predicting ultimate pile bearing capacity using cone penetration test data","display_name":"Developing a new hybrid soft computing technique in predicting ultimate pile bearing capacity using cone penetration test data","publication_year":2020,"publication_date":"2020-01-30","ids":{"openalex":"https://openalex.org/W3003738623","doi":"https://doi.org/10.1017/s0890060420000025","mag":"3003738623"},"language":"en","primary_location":{"id":"doi:10.1017/s0890060420000025","is_oa":false,"landing_page_url":"https://doi.org/10.1017/s0890060420000025","pdf_url":null,"source":{"id":"https://openalex.org/S4210193102","display_name":"Artificial intelligence for engineering design analysis and manufacturing","issn_l":"0890-0604","issn":["0890-0604","1469-1760"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence for Engineering Design, Analysis and Manufacturing","raw_type":"journal-article"},"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/A5053487149","display_name":"Hooman Harandizadeh","orcid":"https://orcid.org/0000-0002-9337-0267"},"institutions":[{"id":"https://openalex.org/I115566878","display_name":"Shahid Bahonar University of Kerman","ror":"https://ror.org/04zn42r77","country_code":"IR","type":"education","lineage":["https://openalex.org/I115566878"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Hooman Harandizadeh","raw_affiliation_strings":["Department of Civil Engineering, Faculty of Engineering, Shahid Bahonar University of Kerman, Pajoohesh Sq., Imam Khomeni Highway, Post Office Box: 76169133, Kerman7616913439, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Faculty of Engineering, Shahid Bahonar University of Kerman, Pajoohesh Sq., Imam Khomeni Highway, Post Office Box: 76169133, Kerman7616913439, Iran","institution_ids":["https://openalex.org/I115566878"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5053487149"],"corresponding_institution_ids":["https://openalex.org/I115566878"],"apc_list":null,"apc_paid":null,"fwci":0.7118,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.67151683,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"34","issue":"1","first_page":"114","last_page":"126"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10264","display_name":"Asphalt Pavement Performance Evaluation","score":0.9783999919891357,"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":0.9783999919891357,"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/T12233","display_name":"Geotechnical Engineering and Underground Structures","score":0.9754999876022339,"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/T10892","display_name":"Drilling and Well Engineering","score":0.973800003528595,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/adaptive-neuro-fuzzy-inference-system","display_name":"Adaptive neuro fuzzy inference system","score":0.8129130005836487},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.7563257217407227},{"id":"https://openalex.org/keywords/pile","display_name":"Pile","score":0.6861217617988586},{"id":"https://openalex.org/keywords/soft-computing","display_name":"Soft computing","score":0.6771448850631714},{"id":"https://openalex.org/keywords/group-method-of-data-handling","display_name":"Group method of data handling","score":0.6592468619346619},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6188895106315613},{"id":"https://openalex.org/keywords/cone-penetration-test","display_name":"Cone penetration test","score":0.5533190965652466},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.4905533194541931},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4338390529155731},{"id":"https://openalex.org/keywords/bearing-capacity","display_name":"Bearing capacity","score":0.42370322346687317},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.3775848150253296},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34520143270492554},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32742005586624146},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2954672873020172},{"id":"https://openalex.org/keywords/structural-engineering","display_name":"Structural engineering","score":0.20032429695129395},{"id":"https://openalex.org/keywords/geotechnical-engineering","display_name":"Geotechnical engineering","score":0.19900211691856384},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.17588698863983154},{"id":"https://openalex.org/keywords/fuzzy-control-system","display_name":"Fuzzy control system","score":0.1359131634235382}],"concepts":[{"id":"https://openalex.org/C186108316","wikidata":"https://www.wikidata.org/wiki/Q352530","display_name":"Adaptive neuro fuzzy inference system","level":4,"score":0.8129130005836487},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.7563257217407227},{"id":"https://openalex.org/C119560385","wikidata":"https://www.wikidata.org/wiki/Q7193850","display_name":"Pile","level":2,"score":0.6861217617988586},{"id":"https://openalex.org/C140073362","wikidata":"https://www.wikidata.org/wiki/Q738759","display_name":"Soft computing","level":3,"score":0.6771448850631714},{"id":"https://openalex.org/C13926793","wikidata":"https://www.wikidata.org/wiki/Q3507155","display_name":"Group method of data handling","level":2,"score":0.6592468619346619},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6188895106315613},{"id":"https://openalex.org/C176071119","wikidata":"https://www.wikidata.org/wiki/Q1261042","display_name":"Cone penetration test","level":2,"score":0.5533190965652466},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.4905533194541931},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4338390529155731},{"id":"https://openalex.org/C135677250","wikidata":"https://www.wikidata.org/wiki/Q3319673","display_name":"Bearing capacity","level":2,"score":0.42370322346687317},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3775848150253296},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34520143270492554},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32742005586624146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2954672873020172},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.20032429695129395},{"id":"https://openalex.org/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","level":1,"score":0.19900211691856384},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.17588698863983154},{"id":"https://openalex.org/C195975749","wikidata":"https://www.wikidata.org/wiki/Q1475705","display_name":"Fuzzy control system","level":3,"score":0.1359131634235382},{"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:10.1017/s0890060420000025","is_oa":false,"landing_page_url":"https://doi.org/10.1017/s0890060420000025","pdf_url":null,"source":{"id":"https://openalex.org/S4210193102","display_name":"Artificial intelligence for engineering design analysis and manufacturing","issn_l":"0890-0604","issn":["0890-0604","1469-1760"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence for Engineering Design, Analysis and Manufacturing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":73,"referenced_works":["https://openalex.org/W116850845","https://openalex.org/W1493287294","https://openalex.org/W1852037277","https://openalex.org/W1916166419","https://openalex.org/W1966864451","https://openalex.org/W1986409279","https://openalex.org/W2016081598","https://openalex.org/W2020858717","https://openalex.org/W2021159928","https://openalex.org/W2042909632","https://openalex.org/W2046421825","https://openalex.org/W2051813988","https://openalex.org/W2052963662","https://openalex.org/W2054400218","https://openalex.org/W2062015870","https://openalex.org/W2069078237","https://openalex.org/W2078137712","https://openalex.org/W2079803814","https://openalex.org/W2080951891","https://openalex.org/W2083523694","https://openalex.org/W2086282769","https://openalex.org/W2094824622","https://openalex.org/W2099969616","https://openalex.org/W2100216851","https://openalex.org/W2101066084","https://openalex.org/W2108702169","https://openalex.org/W2109364787","https://openalex.org/W2139508021","https://openalex.org/W2139898049","https://openalex.org/W2139941099","https://openalex.org/W2153602905","https://openalex.org/W2159265133","https://openalex.org/W2164063121","https://openalex.org/W2228109176","https://openalex.org/W2230017897","https://openalex.org/W2312861422","https://openalex.org/W2333053983","https://openalex.org/W2398317498","https://openalex.org/W2402846924","https://openalex.org/W2405008484","https://openalex.org/W2405709692","https://openalex.org/W2473270311","https://openalex.org/W2473689547","https://openalex.org/W2477348392","https://openalex.org/W2537450119","https://openalex.org/W2543580944","https://openalex.org/W2560696496","https://openalex.org/W2663838451","https://openalex.org/W2737587394","https://openalex.org/W2742563415","https://openalex.org/W2743274700","https://openalex.org/W2747953098","https://openalex.org/W2749827977","https://openalex.org/W2765705722","https://openalex.org/W2767988664","https://openalex.org/W2768643127","https://openalex.org/W2783671650","https://openalex.org/W2789962848","https://openalex.org/W2792789292","https://openalex.org/W2794422582","https://openalex.org/W2803100620","https://openalex.org/W2811353305","https://openalex.org/W2884906162","https://openalex.org/W2891506620","https://openalex.org/W2904857339","https://openalex.org/W4251225685","https://openalex.org/W6604697932","https://openalex.org/W6689135122","https://openalex.org/W6712528286","https://openalex.org/W6747870135","https://openalex.org/W6753344339","https://openalex.org/W6755032153","https://openalex.org/W6757257522"],"related_works":["https://openalex.org/W2114654021","https://openalex.org/W2263529430","https://openalex.org/W3014179099","https://openalex.org/W2022223561","https://openalex.org/W3089083001","https://openalex.org/W2916359391","https://openalex.org/W3196797324","https://openalex.org/W2751094408","https://openalex.org/W2801821709","https://openalex.org/W2592239915"],"abstract_inverted_index":{"Abstract":[0],"This":[1],"research":[2,159],"intends":[3],"to":[4,14,47,90,105,174,194,204,234],"investigate":[5],"a":[6,49,91,206,224],"new":[7,50,92],"hybrid":[8,51,85,93,121],"artificial":[9],"intelligence":[10],"(AI)":[11],"technique":[12],"compared":[13,173,193,233],"some":[15],"common":[16],"CPT":[17,112,176],"methods":[18],"in":[19,33,45,109,197,202,228],"estimating":[20],"axial":[21],"ultimate":[22,255],"pile":[23,106,128,136,254],"bearing":[24,256],"capacity":[25],"(UPBC)":[26],"using":[27],"cone":[28,131],"penetration":[29],"test":[30],"(CPT)":[31],"data":[32,38,67],"geotechnical":[34],"engineering":[35],"applications.":[36],"A":[37],"series":[39],"of":[40,53,65,126,157,199,230],"108":[41],"samples":[42],"was":[43,73,192,215],"collected":[44],"order":[46,203],"develop":[48],"structure":[52],"an":[54,170],"adaptive":[55],"neuro-fuzzy":[56],"inference":[57],"system":[58],"(ANFIS)":[59],"network,":[60],"and":[61,114,138,184,247],"the":[62,66,77,84,119,127,143,152,162,167,211,218],"group":[63],"method":[64],"handling":[68],"(GMDH)":[69],"type":[70],"neural":[71,122],"network":[72,189],"optimized":[74],"by":[75],"applying":[76],"particle":[78],"swarm":[79],"optimization":[80],"(PSO)":[81],"algorithm":[82],"over":[83],"ANFIS-GMDH":[86],"topology,":[87],"which":[88],"leads":[89],"AI":[94],"model":[95,165,190,221],"called":[96],"as":[97,148,239],"ANFIS-GMDH-PSO.":[98],"The":[99,124,155],"derived":[100],"database":[101],"provides":[102],"information":[103,116],"related":[104],"load":[107],"tests,":[108],"situ":[110],"field":[111],"data,":[113],"soil\u2013pile":[115],"for":[117,151,251],"introducing":[118],"proposed":[120,153,163],"system.":[123],"cross-section":[125],"toe,":[129],"average":[130],"tip":[132],"resistance":[133,141],"along":[134,142],"embedded":[135],"length,":[137],"sleeve":[139],"frictional":[140],"shaft":[144],"had":[145],"been":[146],"considered":[147],"input":[149],"parameters":[150],"network.":[154],"results":[156],"this":[158],"indicated":[160],"that":[161,217],"ANFIS-GMDH-PSO":[164,188,220],"predicted":[166],"UPBC":[168],"with":[169],"acceptable":[171],"precision":[172],"various":[175],"methods,":[177,237],"including":[178],"Schmertmann,":[179],"De":[180,242],"Kuiter":[181,243],"&amp;":[182,244,249],"Bringen,":[183],"LPC/LPCT":[185],"methods.":[186],"Moreover,":[187],"performance":[191],"CPT-based":[195,235],"models":[196],"terms":[198,229],"statistical":[200,212,231],"criteria":[201],"achieve":[205],"best":[207],"fitted":[208],"model.":[209],"From":[210],"results,":[213],"it":[214],"found":[216],"developed":[219],"has":[222],"achieved":[223],"higher":[225],"accuracy":[226],"level":[227],"indices":[232],"empirical":[236],"such":[238],"Schmertmann":[240],"model,":[241,246],"Beringen":[245],"Bustamante":[248],"Gianeselli":[250],"predicting":[252],"driven":[253],"capacity.":[257]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
