{"id":"https://openalex.org/W4395057332","doi":"https://doi.org/10.1145/3638884.3638980","title":"An Exponential Transformation Model for Solving Nonlinear Equations Systems","display_name":"An Exponential Transformation Model for Solving Nonlinear Equations Systems","publication_year":2023,"publication_date":"2023-12-14","ids":{"openalex":"https://openalex.org/W4395057332","doi":"https://doi.org/10.1145/3638884.3638980"},"language":"en","primary_location":{"id":"doi:10.1145/3638884.3638980","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3638884.3638980","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 9th International Conference on Communication and Information Processing","raw_type":"proceedings-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/A5050106169","display_name":"Rui Ji","orcid":"https://orcid.org/0009-0005-7641-2292"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Rui Ji","raw_affiliation_strings":["School of Science, Beijing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"School of Science, Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081590963","display_name":"Mingjie Fan","orcid":"https://orcid.org/0000-0002-6226-850X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingjie Fan","raw_affiliation_strings":["School of Science, Beijing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"School of Science, Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101720779","display_name":"Ya Gao","orcid":"https://orcid.org/0009-0002-1775-9569"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ya Gao","raw_affiliation_strings":["School of Science, Beijing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"School of Science, Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050391013","display_name":"Xinchao Zhao","orcid":"https://orcid.org/0000-0001-9376-7646"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinchao Zhao","raw_affiliation_strings":["School of Science, Beijing University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"School of Science, Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5050106169"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.174,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.61385514,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"611","last_page":"616"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10963","display_name":"Advanced Optimization Algorithms Research","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/2612","display_name":"Numerical Analysis"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/exponential-function","display_name":"Exponential function","score":0.7181807160377502},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.6949667930603027},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.6175225377082825},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5569314956665039},{"id":"https://openalex.org/keywords/generality","display_name":"Generality","score":0.5500803589820862},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.5160767436027527},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4992094039916992},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4378577768802643},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.43014898896217346},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4199991822242737},{"id":"https://openalex.org/keywords/model-transformation","display_name":"Model transformation","score":0.4130588471889496},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.37539535760879517},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3734256625175476},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.15997296571731567},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.08555164933204651}],"concepts":[{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.7181807160377502},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.6949667930603027},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6175225377082825},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5569314956665039},{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.5500803589820862},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.5160767436027527},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4992094039916992},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4378577768802643},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.43014898896217346},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4199991822242737},{"id":"https://openalex.org/C2779791154","wikidata":"https://www.wikidata.org/wiki/Q258040","display_name":"Model transformation","level":3,"score":0.4130588471889496},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.37539535760879517},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3734256625175476},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.15997296571731567},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.08555164933204651},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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":1,"locations":[{"id":"doi:10.1145/3638884.3638980","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3638884.3638980","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 9th International Conference on Communication and Information Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1595159159","https://openalex.org/W1968005908","https://openalex.org/W2032079269","https://openalex.org/W2034849564","https://openalex.org/W2046526480","https://openalex.org/W2052045241","https://openalex.org/W2063657280","https://openalex.org/W2081469310","https://openalex.org/W2082462780","https://openalex.org/W2126105956","https://openalex.org/W2138537392","https://openalex.org/W2143381319","https://openalex.org/W3162017678"],"related_works":["https://openalex.org/W2045049461","https://openalex.org/W1978893398","https://openalex.org/W2201908702","https://openalex.org/W4381094582","https://openalex.org/W2369625323","https://openalex.org/W2364579609","https://openalex.org/W1977906818","https://openalex.org/W2034623411","https://openalex.org/W1964286703","https://openalex.org/W2169866437"],"abstract_inverted_index":{"A":[0],"novel":[1],"objective":[2,24],"function":[3,25,115],"transformation":[4,40,45],"model":[5,26,122,157],"based":[6],"on":[7,111],"exponential":[8,54,66,121],"functions":[9,67],"is":[10,56],"proposed":[11,120,156],"to":[12,51,58,70,145,150],"address":[13],"the":[14,23,43,53,60,76,101,112,119,133,151,155],"issue":[15],"of":[16,35,65,89,103],"weak":[17],"specificity":[18],"and":[19,164],"strong":[20],"generality":[21],"in":[22,161],"used":[27],"with":[28,85],"single-objective":[29,39,140],"optimization":[30,141],"algorithms":[31],"for":[32,138],"solving":[33,139],"systems":[34],"nonlinear":[36],"equations":[37],"through":[38],"techniques.":[41],"During":[42],"problem":[44,61],"process,":[46],"this":[47],"new":[48],"model,":[49,55],"referred":[50],"as":[52],"introduced":[57],"effectuate":[59],"transformation.":[62],"Various":[63],"specifications":[64],"are":[68],"employed":[69],"increase":[71],"diversity.":[72],"Subsequently,":[73],"we":[74],"enhance":[75],"selected":[77,113],"algorithm":[78],"by":[79],"incorporating":[80],"a":[81,86],"local":[82,97],"search":[83,136],"method":[84,92],"Gaussian":[87],"coefficient":[88],"0.6.":[90],"This":[91],"involves":[93],"two":[94,152],"searches":[95],"within":[96],"spaces,":[98],"effectively":[99],"facilitating":[100],"identification":[102],"roots":[104],"located":[105],"near":[106],"exceptional":[107],"individuals.":[108],"Experimental":[109],"results":[110],"test":[114],"set":[116],"demonstrate":[117],"that":[118],"not":[123],"only":[124],"entirely":[125],"substitutes":[126],"existing":[127],"models":[128],"but":[129],"also":[130],"significantly":[131],"enhances":[132],"algorithm's":[134],"global":[135],"capability":[137],"problems":[142],"when":[143],"compared":[144,149],"traditional":[146],"models.":[147],"When":[148],"current":[153],"models,":[154],"exhibits":[158],"superior":[159],"performance":[160],"root-finding":[162],"rate":[163],"success":[165],"rate.":[166]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
