{"id":"https://openalex.org/W3175363725","doi":"https://doi.org/10.32604/iasc.2021.018289","title":"Optimal Parameter Estimation of Proton Exchange Membrane Fuel Cells","display_name":"Optimal Parameter Estimation of Proton Exchange Membrane Fuel Cells","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3175363725","doi":"https://doi.org/10.32604/iasc.2021.018289","mag":"3175363725"},"language":"en","primary_location":{"id":"doi:10.32604/iasc.2021.018289","doi":"https://doi.org/10.32604/iasc.2021.018289","is_oa":true,"landing_page_url":"https://doi.org/10.32604/iasc.2021.018289","pdf_url":null,"source":{"id":"https://openalex.org/S40639465","display_name":"Intelligent Automation & Soft Computing","issn_l":"1079-8587","issn":["1079-8587","2326-005X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","jufo-1","norway-1","poland-20","russia-white-list-1"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Automation & Soft Computing","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.32604/iasc.2021.018289","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108134254","display_name":"A. M. Abdullah","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"A. M. Abdullah","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086816810","display_name":"Hegazy Rezk","orcid":"https://orcid.org/0000-0001-9254-2744","observed_orcids":["https://orcid.org/0000-0001-9254-2744"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Hegazy Rezk","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109040923","display_name":"Amir Hossein Hadad","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"A. Hadad","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026846513","display_name":"Mohamed K. Hassan","orcid":"https://orcid.org/0000-0002-5353-3578","observed_orcids":["https://orcid.org/0000-0002-5353-3578"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mohamed K. Hassan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5067851277","display_name":"Ahmed F. Mohamed","orcid":"https://orcid.org/0000-0003-3559-9650","observed_orcids":["https://orcid.org/0000-0003-3559-9650"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"A. F. Mohamed","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5086816810"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8076,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.66183273,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"29","issue":"2","first_page":"619","last_page":"631"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10409","display_name":"Fuel Cells and Related Materials","score":0.9613999724388123,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10409","display_name":"Fuel Cells and Related Materials","score":0.9613999724388123,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.03200000151991844,"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/T11007","display_name":"Hybrid Renewable Energy Systems","score":0.001500000013038516,"subfield":{"id":"https://openalex.org/subfields/2102","display_name":"Energy Engineering and Power Technology"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/proton-exchange-membrane-fuel-cells","display_name":"proton exchange membrane fuel cells","score":0.8999999761581421},{"id":"https://openalex.org/keywords/parameter-estimation","display_name":"parameter estimation","score":0.9120000004768372},{"id":"https://openalex.org/keywords/fuel-cell-modeling","display_name":"fuel cell modeling","score":0.628000020980835},{"id":"https://openalex.org/keywords/sine-cosine-algorithm","display_name":"sine cosine algorithm","score":0.953000009059906},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"particle swarm optimization","score":1.0},{"id":"https://openalex.org/keywords/metaheuristic-optimization","display_name":"metaheuristic optimization","score":0.7149999737739563}],"concepts":[{"id":"https://openalex.org/C132319479","wikidata":"https://www.wikidata.org/wiki/Q899619","display_name":"Proton exchange membrane fuel cell","level":3,"score":0.882422685623169},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.7611846923828125},{"id":"https://openalex.org/C178009071","wikidata":"https://www.wikidata.org/wiki/Q93344","display_name":"Trigonometric functions","level":2,"score":0.5341984629631042},{"id":"https://openalex.org/C186661526","wikidata":"https://www.wikidata.org/wiki/Q13647261","display_name":"Sine","level":2,"score":0.4980902671813965},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.49475568532943726},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4914144277572632},{"id":"https://openalex.org/C22679943","wikidata":"https://www.wikidata.org/wiki/Q159375","display_name":"Standard deviation","level":2,"score":0.4848576784133911},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44981294870376587},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.42369717359542847},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3924359679222107},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3612831234931946},{"id":"https://openalex.org/C2987658370","wikidata":"https://www.wikidata.org/wiki/Q180253","display_name":"Fuel cells","level":2,"score":0.29583728313446045},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2837259769439697},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.25637176632881165},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.18714049458503723},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10229462385177612},{"id":"https://openalex.org/C42360764","wikidata":"https://www.wikidata.org/wiki/Q83588","display_name":"Chemical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/iasc.2021.018289","doi":"https://doi.org/10.32604/iasc.2021.018289","is_oa":true,"landing_page_url":"https://doi.org/10.32604/iasc.2021.018289","pdf_url":null,"source":{"id":"https://openalex.org/S40639465","display_name":"Intelligent Automation & Soft Computing","issn_l":"1079-8587","issn":["1079-8587","2326-005X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","jufo-1","norway-1","poland-20","russia-white-list-1"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Automation & Soft Computing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32604/iasc.2021.018289","doi":"https://doi.org/10.32604/iasc.2021.018289","is_oa":true,"landing_page_url":"https://doi.org/10.32604/iasc.2021.018289","pdf_url":null,"source":{"id":"https://openalex.org/S40639465","display_name":"Intelligent Automation & Soft Computing","issn_l":"1079-8587","issn":["1079-8587","2326-005X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","jufo-1","norway-1","poland-20","russia-white-list-1"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Automation & Soft Computing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.9853000044822693,"id":"https://metadata.un.org/sdg/7"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W883434633","https://openalex.org/W2031783064","https://openalex.org/W2047982693","https://openalex.org/W2101476747","https://openalex.org/W2232317135","https://openalex.org/W2767707525","https://openalex.org/W2897683126","https://openalex.org/W2922249344","https://openalex.org/W3005898487","https://openalex.org/W3011796810","https://openalex.org/W3022510065","https://openalex.org/W3022672521","https://openalex.org/W3025183236","https://openalex.org/W3029242071","https://openalex.org/W3047003773","https://openalex.org/W3118679523","https://openalex.org/W3122283262","https://openalex.org/W3132228393"],"related_works":["https://openalex.org/W4401532922","https://openalex.org/W3083510960","https://openalex.org/W3033670462","https://openalex.org/W4307858645","https://openalex.org/W3025183236","https://openalex.org/W3083506329","https://openalex.org/W4391914218","https://openalex.org/W7117159684","https://openalex.org/W3133850605","https://openalex.org/W3083290725"],"abstract_inverted_index":{"The":[0,90,115,134,152],"problem":[1],"of":[2,5,23,44,64,82,108,158,166],"parameter":[3],"estimation":[4],"the":[6,19,28,41,62,65,68,101,105,109,112,119,124,140,156,159,163,167,177,180,198],"proton":[7],"exchange":[8],"membrane":[9],"fuel":[10],"cell":[11],"(PEMFC)":[12],"model":[13,169],"plays":[14],"a":[15,24,31],"significant":[16],"role":[17],"in":[18,139,161,170],"simulation":[20],"and":[21,53,80,111,129,150,174,186,191,205,210],"optimization":[22,34,69,132],"PEMFC":[25,83,110,168,195],"system.":[26],"In":[27],"current":[29],"research,":[30],"moth":[32],"flame":[33],"algorithm":[35,127],"(MFOA)":[36],"is":[37,98],"used":[38,59],"to":[39,60,86,95],"identify":[40],"best":[42,142,164],"parameters":[43,73,165],"PEMFC.":[45],"Two":[46],"different":[47],"PEMFCs,":[48],"Nedstack":[49,178],"PS6,":[50,179],"6":[51],"kW,":[52],"SR-12":[54],"PEM":[55],"500":[56],"W":[57],"are":[58,84,121,137,183,202],"demonstrate":[61],"accuracy":[63],"MFOA.":[66],"Throughout":[67],"process,":[70],"seven":[71],"unidentified":[72],"(\u21251,":[74],"\u21252,":[75],"\u21253,":[76],"\u21254,":[77],"\u03bb,":[78],"\u211b,":[79],"B)":[81],"appointed":[85],"be":[87,96],"decision":[88],"variables.":[89],"fitness":[91],"function,":[92],"which":[93],"needed":[94],"minimum,":[97],"represented":[99],"by":[100,118],"root-mean-square":[102],"error":[103],"between":[104],"calculated":[106],"voltage":[107],"experimental":[113],"dataset.":[114],"results":[116],"attained":[117],"MFOA":[120,160],"compared":[122],"with":[123,172],"sine":[125],"cosine":[126],"(SCA)":[128],"particle":[130],"swarm":[131],"(PSO).":[133],"following":[135],"metrics":[136],"considered":[138],"comparison:":[141],"value,":[143,145,147],"worst":[144],"average":[146,199],"standard":[148],"deviation,":[149],"efficiency.":[151],"main":[153],"findings":[154],"verified":[155],"supremacy":[157],"estimating":[162],"comparison":[171],"PSO":[173,190],"SCA.":[175],"For":[176,194],"efficiency":[181,200],"values":[182,201],"24.50458%,":[184],"79.477%,":[185],"38.84747%":[187],"for":[188,207],"MFOA,":[189,208],"SCA,":[192,211],"respectively.":[193,212],"(SR-12":[196],"PEM),":[197],"14.965%,":[203],"79.933%":[204],"31.87%":[206],"PSO,":[209]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2021-07-05T00:00:00"}