{"id":"https://openalex.org/W3041450954","doi":"https://doi.org/10.1109/access.2020.3008176","title":"A Comparative Study of Inversion Optimization Algorithms for Underground Metal Target Detection","display_name":"A Comparative Study of Inversion Optimization Algorithms for Underground Metal Target Detection","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3041450954","doi":"https://doi.org/10.1109/access.2020.3008176","mag":"3041450954"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3008176","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3008176","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2020.3008176","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111411738","display_name":"Yadong Wan","orcid":null},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yadong Wan","raw_affiliation_strings":["School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100422336","display_name":"Zhen Wang","orcid":"https://orcid.org/0000-0002-4619-9655"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Wang","raw_affiliation_strings":["School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4619-9655","affiliations":[{"raw_affiliation_string":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100396022","display_name":"Peng Wang","orcid":"https://orcid.org/0000-0002-3748-5545"},"institutions":[{"id":"https://openalex.org/I4210162623","display_name":"Datang Telecom Group (China)","ror":"https://ror.org/050rf2257","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210162623"]},{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Wang","raw_affiliation_strings":["Datang Gohigh Data Networks Technology Company Ltd., Beijing, China","School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3748-5545","affiliations":[{"raw_affiliation_string":"Datang Gohigh Data Networks Technology Company Ltd., Beijing, China","institution_ids":["https://openalex.org/I4210162623"]},{"raw_affiliation_string":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100460173","display_name":"Chao Zhang","orcid":"https://orcid.org/0000-0002-4112-1939"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Zhang","raw_affiliation_strings":["School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035752099","display_name":"Shihong Duan","orcid":"https://orcid.org/0000-0001-8162-4269"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shihong Duan","raw_affiliation_strings":["School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100368213","display_name":"Na Li","orcid":"https://orcid.org/0000-0002-4627-036X"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Na Li","raw_affiliation_strings":["School of Mathematics and Physics, University of Science and Technology Beijing, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Physics, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.9057,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.73674106,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"8","issue":null,"first_page":"126401","last_page":"126413"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11609","display_name":"Geophysical Methods and Applications","score":0.9998000264167786,"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/T11609","display_name":"Geophysical Methods and Applications","score":0.9998000264167786,"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/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T10572","display_name":"Geophysical and Geoelectrical Methods","score":0.9994000196456909,"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/algorithm","display_name":"Algorithm","score":0.7579336166381836},{"id":"https://openalex.org/keywords/broyden\u2013fletcher\u2013goldfarb\u2013shanno-algorithm","display_name":"Broyden\u2013Fletcher\u2013Goldfarb\u2013Shanno algorithm","score":0.7230509519577026},{"id":"https://openalex.org/keywords/conjugate-gradient-method","display_name":"Conjugate gradient method","score":0.7009227871894836},{"id":"https://openalex.org/keywords/nonlinear-conjugate-gradient-method","display_name":"Nonlinear conjugate gradient method","score":0.6539506912231445},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.6140665411949158},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5773589611053467},{"id":"https://openalex.org/keywords/least-squares-function-approximation","display_name":"Least-squares function approximation","score":0.5011460781097412},{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.4912335276603699},{"id":"https://openalex.org/keywords/non-linear-least-squares","display_name":"Non-linear least squares","score":0.48054438829421997},{"id":"https://openalex.org/keywords/levenberg\u2013marquardt-algorithm","display_name":"Levenberg\u2013Marquardt algorithm","score":0.4793058931827545},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.42236435413360596},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.377536416053772},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.3124167323112488},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25551581382751465},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1032208502292633},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.09050709009170532},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07295817136764526},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.07294750213623047}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.7579336166381836},{"id":"https://openalex.org/C132721684","wikidata":"https://www.wikidata.org/wiki/Q2877013","display_name":"Broyden\u2013Fletcher\u2013Goldfarb\u2013Shanno algorithm","level":3,"score":0.7230509519577026},{"id":"https://openalex.org/C81184566","wikidata":"https://www.wikidata.org/wiki/Q1191895","display_name":"Conjugate gradient method","level":2,"score":0.7009227871894836},{"id":"https://openalex.org/C26362088","wikidata":"https://www.wikidata.org/wiki/Q17086453","display_name":"Nonlinear conjugate gradient method","level":4,"score":0.6539506912231445},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.6140665411949158},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5773589611053467},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.5011460781097412},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.4912335276603699},{"id":"https://openalex.org/C45923927","wikidata":"https://www.wikidata.org/wiki/Q3319230","display_name":"Non-linear least squares","level":3,"score":0.48054438829421997},{"id":"https://openalex.org/C87578567","wikidata":"https://www.wikidata.org/wiki/Q1426494","display_name":"Levenberg\u2013Marquardt algorithm","level":3,"score":0.4793058931827545},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.42236435413360596},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.377536416053772},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.3124167323112488},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25551581382751465},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1032208502292633},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.09050709009170532},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07295817136764526},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.07294750213623047},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C109007969","wikidata":"https://www.wikidata.org/wiki/Q749565","display_name":"Structural basin","level":2,"score":0.0},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3008176","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3008176","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:f73906d4f7374e519dedfa3d65367442","is_oa":true,"landing_page_url":"https://doaj.org/article/f73906d4f7374e519dedfa3d65367442","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":"IEEE Access, Vol 8, Pp 126401-126413 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3008176","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3008176","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.44999998807907104}],"awards":[{"id":"https://openalex.org/G4853966892","display_name":null,"funder_award_id":"2019M650778","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G6993100060","display_name":null,"funder_award_id":"2302018FRF-GF-18-016B","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G708827205","display_name":"\u9762\u5411\u590d\u6742\u5efa\u7b51\u73af\u5883\u6d88\u9632\u5458\u5e94\u6025\u5b9a\u4f4d\u7684TOA\u4fe1\u53f7\u4f20\u8f93\u6a21\u578b\u548c\u5173\u952e\u7b97\u6cd5\u7814\u7a76","funder_award_id":"61671056","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W100464641","https://openalex.org/W128143863","https://openalex.org/W311385830","https://openalex.org/W1964631981","https://openalex.org/W1972898532","https://openalex.org/W2026645785","https://openalex.org/W2038821639","https://openalex.org/W2052151084","https://openalex.org/W2088765131","https://openalex.org/W2090351291","https://openalex.org/W2096927741","https://openalex.org/W2135809864","https://openalex.org/W2163381613","https://openalex.org/W2296370939","https://openalex.org/W2327245997","https://openalex.org/W2523246573","https://openalex.org/W2547282962","https://openalex.org/W2549279661","https://openalex.org/W2557172211","https://openalex.org/W2560690387","https://openalex.org/W2571208790","https://openalex.org/W2577509876","https://openalex.org/W2592440258","https://openalex.org/W2745190785","https://openalex.org/W2799686972","https://openalex.org/W2888158921","https://openalex.org/W2893977378","https://openalex.org/W2901044158","https://openalex.org/W2945189108","https://openalex.org/W2945495670","https://openalex.org/W2973279931","https://openalex.org/W2978227947","https://openalex.org/W2978637301","https://openalex.org/W2978721141","https://openalex.org/W2995161752","https://openalex.org/W2998324027","https://openalex.org/W3099241826","https://openalex.org/W3183873312","https://openalex.org/W4301909677","https://openalex.org/W6663348740","https://openalex.org/W6727249380","https://openalex.org/W6755019448","https://openalex.org/W6755125153","https://openalex.org/W6771688297","https://openalex.org/W6798590141"],"related_works":["https://openalex.org/W2906115589","https://openalex.org/W2272058142","https://openalex.org/W2051800432","https://openalex.org/W3210179682","https://openalex.org/W2018215034","https://openalex.org/W2156273800","https://openalex.org/W1984722404","https://openalex.org/W2136780394","https://openalex.org/W2078029965","https://openalex.org/W1981556389"],"abstract_inverted_index":{"Underground":[0],"metal":[1,11,65,199],"target":[2,66],"detection":[3],"refers":[4],"to":[5,71,111,167],"estimating":[6],"the":[7,25,29,34,39,53,56,61,73,84,87,102,113,173,183,195,202,206,211,220,231,234,242,245],"properties":[8,196],"of":[9,17,46,55,63,75,86,123,125,178,197,214,223,233,244],"underground":[10,64,198],"targets":[12,200],"based":[13],"on":[14],"a":[15],"set":[16],"observed":[18,169],"data.":[19],"Electromagnetic":[20],"induction":[21],"(EMI)":[22],"method":[23,32,37,157],"and":[24,33,95,106,121,137,158,171,187,192,201,210,236],"least-squares":[26,47,57],"inversion":[27],"provide":[28],"data":[30,140,170],"acquisition":[31,141],"parameter":[35],"estimation":[36,117],"for":[38],"detection,":[40,67],"respectively.":[41],"As":[42],"an":[43],"important":[44],"part":[45],"inversion,":[48],"optimization":[49,77,128,174,225,246],"algorithms":[50,129,144],"directly":[51],"affect":[52,241],"efficiency":[54,62,243],"inversion.":[58],"To":[59],"improve":[60],"it":[68],"is":[69],"necessary":[70],"compare":[72,172],"performance":[74],"different":[76,133,139],"algorithms.":[78,175,247],"In":[79],"this":[80],"paper,":[81],"we":[82,217],"analyzed":[83,219],"characteristic":[85],"complex":[88],"EMI":[89,103],"forward":[90,104],"model":[91,105],"using":[92],"sensitivity":[93,97],"analysis":[94,98],"inverse":[96],"at":[99],"first.":[100],"Then,":[101],"least":[107,212],"squares":[108],"were":[109,130],"used":[110],"build":[112],"objective":[114],"function.":[115],"The":[116,143,176,227],"error,":[118],"run":[119,208],"time":[120,209,221],"number":[122,213],"iterations":[124],"six":[126],"numerical":[127],"compared":[131],"under":[132,138],"signal-to-noise":[134],"ratios":[135],"(SNRs)":[136],"spacing.":[142],"include":[145],"gradient":[146,156,186,235],"descent,":[147,149],"steepest":[148],"Newton's":[150],"method,":[151],"Broyden-Fletcher-Goldfarb-Shanno":[152],"(BFGS)":[153],"algorithm,":[154],"conjugate":[155,185],"Levenberg-Marquardt":[159],"(LM)":[160],"algorithm.":[161,226],"A":[162],"simulation":[163],"platform":[164],"was":[165],"established":[166],"generate":[168],"results":[177,228],"algorithm":[179,189,204],"comparison":[180],"showed":[181],"that":[182,230],"BFGS,":[184],"LM":[188,203],"can":[190],"efficiently":[191],"accurately":[193],"estimate":[194],"has":[205],"shortest":[207],"iterations.":[215],"Finally,":[216],"carefully":[218],"consumption":[222],"each":[224],"show":[229],"calculation":[232],"step":[237],"length":[238],"selection":[239],"greatly":[240]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}