{"id":"https://openalex.org/W3115545947","doi":"https://doi.org/10.1109/vcip49819.2020.9301849","title":"Machine Learning for Photometric Redshift Estimation of Quasars with Different Samples","display_name":"Machine Learning for Photometric Redshift Estimation of Quasars with Different Samples","publication_year":2020,"publication_date":"2020-12-01","ids":{"openalex":"https://openalex.org/W3115545947","doi":"https://doi.org/10.1109/vcip49819.2020.9301849","mag":"3115545947"},"language":"en","primary_location":{"id":"doi:10.1109/vcip49819.2020.9301849","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip49819.2020.9301849","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)","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/A5100712432","display_name":"Yanxia Zhang","orcid":"https://orcid.org/0000-0002-6610-5265"},"institutions":[{"id":"https://openalex.org/I4210164580","display_name":"National Astronomical Observatories","ror":"https://ror.org/058pyyv44","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210164580"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yanxia Zhang","raw_affiliation_strings":["CAS Key Laboratory of Optical Astronomy, National Astronomical Observatories, Beijing, China"],"affiliations":[{"raw_affiliation_string":"CAS Key Laboratory of Optical Astronomy, National Astronomical Observatories, Beijing, China","institution_ids":["https://openalex.org/I4210164580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100641350","display_name":"Xin Jin","orcid":"https://orcid.org/0000-0003-2211-2006"},"institutions":[{"id":"https://openalex.org/I4210164580","display_name":"National Astronomical Observatories","ror":"https://ror.org/058pyyv44","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210164580"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Jin","raw_affiliation_strings":["CAS Key Laboratory of Optical Astronomy, National Astronomical Observatories, Beijing, China"],"affiliations":[{"raw_affiliation_string":"CAS Key Laboratory of Optical Astronomy, National Astronomical Observatories, Beijing, China","institution_ids":["https://openalex.org/I4210164580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100458626","display_name":"Jingyi Zhang","orcid":"https://orcid.org/0000-0002-7048-0930"},"institutions":[{"id":"https://openalex.org/I4210164580","display_name":"National Astronomical Observatories","ror":"https://ror.org/058pyyv44","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210164580"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyi Zhang","raw_affiliation_strings":["CAS Key Laboratory of Optical Astronomy, National Astronomical Observatories, Beijing, China"],"affiliations":[{"raw_affiliation_string":"CAS Key Laboratory of Optical Astronomy, National Astronomical Observatories, Beijing, China","institution_ids":["https://openalex.org/I4210164580"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100458721","display_name":"Yongheng Zhao","orcid":"https://orcid.org/0000-0001-5298-2833"},"institutions":[{"id":"https://openalex.org/I4210164580","display_name":"National Astronomical Observatories","ror":"https://ror.org/058pyyv44","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210164580"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongheng Zhao","raw_affiliation_strings":["CAS Key Laboratory of Optical Astronomy, National Astronomical Observatories, Beijing, China"],"affiliations":[{"raw_affiliation_string":"CAS Key Laboratory of Optical Astronomy, National Astronomical Observatories, Beijing, China","institution_ids":["https://openalex.org/I4210164580"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100712432"],"corresponding_institution_ids":["https://openalex.org/I4210164580"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16175029,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"319","issue":null,"first_page":"294","last_page":"297"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10026","display_name":"Galaxies: Formation, Evolution, Phenomena","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/3103","display_name":"Astronomy and Astrophysics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10026","display_name":"Galaxies: Formation, Evolution, Phenomena","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/3103","display_name":"Astronomy and Astrophysics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9836999773979187,"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/T14163","display_name":"Astronomical Observations and Instrumentation","score":0.9825000166893005,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/random-forest","display_name":"Random forest","score":0.8470704555511475},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.6844261288642883},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.6784806847572327},{"id":"https://openalex.org/keywords/photometric-redshift","display_name":"Photometric redshift","score":0.6528459787368774},{"id":"https://openalex.org/keywords/redshift","display_name":"Redshift","score":0.6498210430145264},{"id":"https://openalex.org/keywords/quasar","display_name":"Quasar","score":0.6296700835227966},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5383085012435913},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5030121207237244},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4841897785663605},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45638468861579895},{"id":"https://openalex.org/keywords/astrophysics","display_name":"Astrophysics","score":0.4149520993232727},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.25117385387420654}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.8470704555511475},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.6844261288642883},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.6784806847572327},{"id":"https://openalex.org/C2780974285","wikidata":"https://www.wikidata.org/wiki/Q3967221","display_name":"Photometric redshift","level":4,"score":0.6528459787368774},{"id":"https://openalex.org/C33024259","wikidata":"https://www.wikidata.org/wiki/Q76250","display_name":"Redshift","level":3,"score":0.6498210430145264},{"id":"https://openalex.org/C135041427","wikidata":"https://www.wikidata.org/wiki/Q83373","display_name":"Quasar","level":3,"score":0.6296700835227966},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5383085012435913},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5030121207237244},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4841897785663605},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45638468861579895},{"id":"https://openalex.org/C44870925","wikidata":"https://www.wikidata.org/wiki/Q37547","display_name":"Astrophysics","level":1,"score":0.4149520993232727},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.25117385387420654},{"id":"https://openalex.org/C98444146","wikidata":"https://www.wikidata.org/wiki/Q318","display_name":"Galaxy","level":2,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vcip49819.2020.9301849","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip49819.2020.9301849","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.44999998807907104}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2010191884","https://openalex.org/W2052384136","https://openalex.org/W2056132907","https://openalex.org/W2080691528","https://openalex.org/W2156909104","https://openalex.org/W2295598076","https://openalex.org/W2514428661","https://openalex.org/W2618871161","https://openalex.org/W2623459029","https://openalex.org/W2768348081","https://openalex.org/W2772195293","https://openalex.org/W2772458775","https://openalex.org/W2911964244","https://openalex.org/W2949107259","https://openalex.org/W2988472346","https://openalex.org/W3102476541","https://openalex.org/W3103927840","https://openalex.org/W3124271762","https://openalex.org/W3182399795","https://openalex.org/W6726208876","https://openalex.org/W6738645361","https://openalex.org/W6745609711","https://openalex.org/W6770227250","https://openalex.org/W6798815426"],"related_works":["https://openalex.org/W2063908823","https://openalex.org/W4245324564","https://openalex.org/W4365456836","https://openalex.org/W4387341579","https://openalex.org/W3125637177","https://openalex.org/W2021442228","https://openalex.org/W2041294110","https://openalex.org/W4244234179","https://openalex.org/W1983041714","https://openalex.org/W2982789411"],"abstract_inverted_index":{"We":[0],"compare":[1],"the":[2,17,25,57,69,76,89,92,95],"performance":[3,70,97],"of":[4,21,71],"Support":[5],"Vector":[6],"Machine,":[7],"XGBoost,":[8],"LightGBM,":[9],"k-Nearest":[10,38,48],"Neighbors,":[11,39,49],"Random":[12,40,50],"forests":[13,41,51],"and":[14,42,52,62,83],"Extra-Trees":[15,43,53],"on":[16,24,56,75,112],"photometric":[18],"redshift":[19],"estimation":[20],"quasars":[22],"based":[23],"SDSS_WISE":[26],"sample.":[27,114],"For":[28],"this":[29],"sample,":[30,91],"LightGBM":[31],"shows":[32,103,109],"its":[33,110],"superiority":[34,111],"in":[35],"speed":[36],"while":[37],"show":[44,67],"better":[45,96],"performance.":[46],"Then":[47],"are":[54],"applied":[55],"SDSS,":[58],"SDSS_WISE,":[59],"SDSS_UKIDSS,":[60],"WISE_UKIDSS":[61],"SDSS_WISE_UKIDSS":[63],"samples.":[64],"The":[65],"results":[66],"that":[68],"an":[72],"algorithm":[73,108],"depends":[74],"sample":[77,79],"selection,":[78],"size,":[80],"input":[81],"pattern":[82],"information":[84,94],"from":[85],"different":[86,101,104],"bands;":[87],"for":[88],"same":[90],"more":[93],"is":[98],"obtained,":[99],"but":[100],"algorithms":[102],"accuracy;":[105],"no":[106],"single":[107],"every":[113]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}