乐胖代购免代理版

{"id":"https://openalex.org/W2056352423","doi":"https://doi.org/10.1109/ijcnn.2012.6252615","title":"Chebyshev Functional Link Neural Network-based modeling and experimental verification for photovoltaic arrays","display_name":"Chebyshev Functional Link Neural Network-based modeling and experimental verification for photovoltaic arrays","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W2056352423","doi":"https://doi.org/10.1109/ijcnn.2012.6252615","mag":"2056352423"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2012.6252615","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5100891158","display_name":"Lian Lian Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Lian Lian Jiang","raw_affiliation_strings":["School of Computer Engineering, Nanyang Technological University,,Singapore"],"affiliations":[{"raw_affiliation_string":"School of Computer Engineering, Nanyang Technological University,,Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059218594","display_name":"Douglas L. Maskell","orcid":"https://orcid.org/0000-0002-6588-4762"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Douglas L. Maskell","raw_affiliation_strings":["School of Computer Engineering, Nanyang Technological University,,Singapore"],"affiliations":[{"raw_affiliation_string":"School of Computer Engineering, Nanyang Technological University,,Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049913930","display_name":"Jagdish C. Patra","orcid":"https://orcid.org/0000-0002-6257-0469"},"institutions":[{"id":"https://openalex.org/I57093077","display_name":"Swinburne University of Technology","ror":"https://ror.org/031rekg67","country_code":"AU","type":"education","lineage":["https://openalex.org/I57093077"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jagdish C. Patra","raw_affiliation_strings":["Faculty of Engineering and Industrial Sciences, Swinburne University of Technology, Hawthorn, Australia#TAB#"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering and Industrial Sciences, Swinburne University of Technology, Hawthorn, Australia#TAB#","institution_ids":["https://openalex.org/I57093077"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.033,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":20,"citation_normalized_percentile":{"value":0.904542,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":90},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10468","display_name":"Photovoltaic System Optimization Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2105","display_name":"Renewable Energy, Sustainability and the Environment"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10468","display_name":"Photovoltaic System Optimization Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2105","display_name":"Renewable Energy, Sustainability and the Environment"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11276","display_name":"Solar Radiation and Photovoltaics","score":0.9943,"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/T12309","display_name":"solar cell performance optimization","score":0.99,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.6037014},{"id":"https://openalex.org/keywords/network-model","display_name":"Network model","score":0.46360055},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.46264684},{"id":"https://openalex.org/keywords/behavioral-modeling","display_name":"Behavioral Modeling","score":0.4485322}],"concepts":[{"id":"https://openalex.org/C41291067","wikidata":"https://www.wikidata.org/wiki/Q1897785","display_name":"Photovoltaic system","level":2,"score":0.7388001},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.71799386},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7123436},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.6037014},{"id":"https://openalex.org/C21424316","wikidata":"https://www.wikidata.org/wiki/Q718621","display_name":"Chebyshev filter","level":2,"score":0.4898121},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.46360055},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.46264684},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.45349842},{"id":"https://openalex.org/C129785596","wikidata":"https://www.wikidata.org/wiki/Q619511","display_name":"Chebyshev polynomials","level":2,"score":0.4521466},{"id":"https://openalex.org/C78639753","wikidata":"https://www.wikidata.org/wiki/Q3318160","display_name":"Behavioral modeling","level":2,"score":0.4485322},{"id":"https://openalex.org/C9695528","wikidata":"https://www.wikidata.org/wiki/Q7556707","display_name":"Solar irradiance","level":2,"score":0.4405299},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39236298},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35788417},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.3280195},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1389432},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10380399},{"id":"https://openalex.org/C91586092","wikidata":"https://www.wikidata.org/wiki/Q757520","display_name":"Atmospheric sciences","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2012.6252615","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.73,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":17,"referenced_works":["https://openalex.org/W1981047769","https://openalex.org/W1992079190","https://openalex.org/W1997988740","https://openalex.org/W2000209454","https://openalex.org/W2003828779","https://openalex.org/W2021750971","https://openalex.org/W2029259196","https://openalex.org/W2032423175","https://openalex.org/W2041437331","https://openalex.org/W2069338754","https://openalex.org/W2079995640","https://openalex.org/W2111809410","https://openalex.org/W2126885794","https://openalex.org/W2131841686","https://openalex.org/W2132507811","https://openalex.org/W2135791206","https://openalex.org/W2144584868"],"related_works":["https://openalex.org/W4213342932","https://openalex.org/W3153890349","https://openalex.org/W3149552330","https://openalex.org/W2541927208","https://openalex.org/W2390710574","https://openalex.org/W2382532955","https://openalex.org/W2106962382","https://openalex.org/W2074316639","https://openalex.org/W2056379897","https://openalex.org/W2010728213"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,22,101,121,215],"Chebyshev":[4],"Functional":[5],"Link":[6],"Neural":[7,34],"Network":[8,35],"(CFLNN)":[9],"based":[10,37,123],"model":[11,23,51,124,130,212],"for":[12,125],"photovoltaic":[13,72],"modules.":[14,127],"There":[15],"are":[16,85],"two":[17,177],"basic":[18],"approaches":[19],"to":[20,115,140,209],"build":[21],"-":[24,180],"use":[25,31],"an":[26,32],"analytical":[27,42,59,157,211],"modeling":[28,43,158,178,199],"technique":[29,44],"or":[30],"Artificial":[33],"(ANN)":[36],"method.":[38,159],"However,":[39],"both":[40],"the":[41,46,58,61,71,76,91,94,107,134,137,141,147,156,161,164,173,183,197,205,210,220],"and":[45,65,78,81,109,182,213],"traditional":[47,221],"Multilayer":[48],"Perceptron":[49],"(MLP)":[50],"have":[52],"some":[53,68],"disadvantages.":[54],"For":[55],"example,":[56],"in":[57,105,110,146],"model,":[60,98],"influence":[62],"of":[63,70,93,136,143,204],"irradiance":[64],"temperature":[66],"on":[67],"parameters":[69],"module,":[73],"such":[74],"as":[75],"parallel":[77],"series":[79],"resistance":[80],"other":[82,176],"uncertainty":[83],"factors,":[84],"not":[86,131],"taken":[87],"into":[88],"consideration.":[89],"In":[90,113,160],"case":[92],"multilayer":[95],"neural":[96],"network":[97,108,138,148],"there":[99],"is":[100,170,188],"large":[102],"computational":[103,217],"complexity":[104,135,218],"training":[106],"its":[111],"implementation.":[112],"order":[114],"overcome":[116],"these":[117],"advantages,":[118],"we":[119],"propose":[120],"CFLNN":[122,169,198],"solar":[126],"The":[128,193],"proposed":[129],"only":[132],"reduces":[133],"due":[139],"absence":[142],"hidden":[144],"layers":[145],"configuration,":[149],"but":[150],"also":[151],"shows":[152],"better":[153,202],"accuracy":[154],"over":[155],"experimental":[162,191],"section,":[163],"operating":[165],"current":[166,207],"predicted":[167],"by":[168],"compared":[171,208],"with":[172],"outputs":[174],"from":[175],"methods":[179],"MLP":[181,222],"two-diode":[184],"model.":[185,223],"Finally,":[186],"verification":[187],"performed":[189],"using":[190],"datasets.":[192],"results":[194],"show":[195],"that":[196],"method":[200],"provides":[201],"prediction":[203],"output":[206],"has":[214],"reduced":[216],"than":[219]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2056352423","counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2025-01-05T06:53:54.614279","created_date":"2016-06-24"}