{"id":"https://openalex.org/W4387615978","doi":"https://doi.org/10.1080/13658816.2023.2266493","title":"Extending regionalization algorithms to explore spatial process heterogeneity","display_name":"Extending regionalization algorithms to explore spatial process heterogeneity","publication_year":2023,"publication_date":"2023-10-13","ids":{"openalex":"https://openalex.org/W4387615978","doi":"https://doi.org/10.1080/13658816.2023.2266493"},"language":"en","primary_location":{"id":"doi:10.1080/13658816.2023.2266493","is_oa":false,"landing_page_url":"https://doi.org/10.1080/13658816.2023.2266493","pdf_url":null,"source":{"id":"https://openalex.org/S4210181446","display_name":"International Journal of Geographical Information Systems","issn_l":"0269-3798","issn":["0269-3798","1362-3087"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Geographical Information Science","raw_type":"journal-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/A5074760707","display_name":"Hao Guo","orcid":"https://orcid.org/0000-0001-7865-546X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Guo","raw_affiliation_strings":["Beijing Key Lab of Spatial Information Integration and Its Applications, Peking University, Beijing, China","Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Lab of Spatial Information Integration and Its Applications, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045331325","display_name":"Andr\u00e9 Python","orcid":"https://orcid.org/0000-0001-8094-7226"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Andre Python","raw_affiliation_strings":["Center for Data Science, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Center for Data Science, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100345691","display_name":"Yu Liu","orcid":"https://orcid.org/0000-0002-0016-2902"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yu Liu","raw_affiliation_strings":["Beijing Key Lab of Spatial Information Integration and Its Applications, Peking University, Beijing, China","Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing, China","Southwest United Graduate School, Kunming, China","State Key Laboratory of Media Convergence Production Technology and Systems, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Lab of Spatial Information Integration and Its Applications, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Southwest United Graduate School, Kunming, China","institution_ids":[]},{"raw_affiliation_string":"State Key Laboratory of Media Convergence Production Technology and Systems, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100345691"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":7.4227,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.96807902,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"37","issue":"11","first_page":"2319","last_page":"2344"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11911","display_name":"Spatial and Panel Data Analysis","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11911","display_name":"Spatial and Panel Data Analysis","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10226","display_name":"Land Use and Ecosystem Services","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11014","display_name":"Regional Economics and Spatial Analysis","score":0.9879000186920166,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6389952301979065},{"id":"https://openalex.org/keywords/toolbox","display_name":"Toolbox","score":0.628307580947876},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5729556679725647},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.5415892601013184},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5380617380142212},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44763243198394775},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.44433730840682983},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.43872907757759094},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4307026267051697},{"id":"https://openalex.org/keywords/constructive","display_name":"Constructive","score":0.4274091124534607},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.39235275983810425},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.34270384907722473},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3278122544288635},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16818606853485107},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.08318924903869629}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6389952301979065},{"id":"https://openalex.org/C2777655017","wikidata":"https://www.wikidata.org/wiki/Q1501161","display_name":"Toolbox","level":2,"score":0.628307580947876},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5729556679725647},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.5415892601013184},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5380617380142212},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44763243198394775},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.44433730840682983},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.43872907757759094},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4307026267051697},{"id":"https://openalex.org/C2778701210","wikidata":"https://www.wikidata.org/wiki/Q28130034","display_name":"Constructive","level":3,"score":0.4274091124534607},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.39235275983810425},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.34270384907722473},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3278122544288635},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16818606853485107},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.08318924903869629},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/13658816.2023.2266493","is_oa":false,"landing_page_url":"https://doi.org/10.1080/13658816.2023.2266493","pdf_url":null,"source":{"id":"https://openalex.org/S4210181446","display_name":"International Journal of Geographical Information Systems","issn_l":"0269-3798","issn":["0269-3798","1362-3087"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Geographical Information Science","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1828651615","display_name":null,"funder_award_id":"2021YFC2701905","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G4294447146","display_name":null,"funder_award_id":"41830645, 41971331, 82273731","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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W176785629","https://openalex.org/W769455669","https://openalex.org/W1533459960","https://openalex.org/W1952692938","https://openalex.org/W1968018625","https://openalex.org/W1973749534","https://openalex.org/W1976840258","https://openalex.org/W1984121786","https://openalex.org/W1984536024","https://openalex.org/W1986062321","https://openalex.org/W1987198424","https://openalex.org/W1990433983","https://openalex.org/W2021557681","https://openalex.org/W2028226037","https://openalex.org/W2033403400","https://openalex.org/W2044579605","https://openalex.org/W2047120335","https://openalex.org/W2050833450","https://openalex.org/W2058529928","https://openalex.org/W2061500022","https://openalex.org/W2065175032","https://openalex.org/W2067344376","https://openalex.org/W2087812927","https://openalex.org/W2089743085","https://openalex.org/W2101234009","https://openalex.org/W2107218399","https://openalex.org/W2117746342","https://openalex.org/W2118049491","https://openalex.org/W2127218421","https://openalex.org/W2127236490","https://openalex.org/W2131124699","https://openalex.org/W2136347018","https://openalex.org/W2139839146","https://openalex.org/W2141585940","https://openalex.org/W2151674328","https://openalex.org/W2162833336","https://openalex.org/W2266085261","https://openalex.org/W2315666945","https://openalex.org/W2343188872","https://openalex.org/W2521357909","https://openalex.org/W2558993060","https://openalex.org/W2747207142","https://openalex.org/W2763546368","https://openalex.org/W2904335155","https://openalex.org/W2912855477","https://openalex.org/W2948613401","https://openalex.org/W2949511096","https://openalex.org/W3021334113","https://openalex.org/W3099930399","https://openalex.org/W3105372924","https://openalex.org/W3114352927","https://openalex.org/W3127218335","https://openalex.org/W3134229995","https://openalex.org/W3142644950","https://openalex.org/W3143479390","https://openalex.org/W3167466924","https://openalex.org/W3171405804","https://openalex.org/W3194059001","https://openalex.org/W3213758364","https://openalex.org/W4206473073","https://openalex.org/W4304003163","https://openalex.org/W4366547277","https://openalex.org/W6675354045","https://openalex.org/W6885069329"],"related_works":["https://openalex.org/W2068663075","https://openalex.org/W2797837731","https://openalex.org/W2978678743","https://openalex.org/W2150344375","https://openalex.org/W829257147","https://openalex.org/W3081389670","https://openalex.org/W4385302116","https://openalex.org/W3044929382","https://openalex.org/W2603075122","https://openalex.org/W1975795843"],"abstract_inverted_index":{"AbstractIn":[0],"spatial":[1,4,45,50,65,82,135,140,237,244,753,759,806,823],"regression":[2,83,146,261],"models,":[3],"heterogeneity":[5],"may":[6,408,574],"be":[7,209,435,510,575],"considered":[8,273],"with":[9,25,373,490,660],"either":[10],"continuous":[11],"or":[12,108,214,336,378,399],"discrete":[13],"specifications.":[14],"The":[15,85,162,452,636],"latter":[16],"is":[17,206,253,279,282,322,346,352,396,401,415,459,463,471,481,533,559,564,586,598,628,655,713,763,827],"related":[18],"to":[19,48,80,90,111,138,208,288,325,348,405,501,514,553,630,634,813],"delineation":[20],"of":[21,44,93,151,182,197,236,272,303,312,355,413,427,447,455,467,475,521,572,581,601,670,684,706,721,788,797,822,832,837],"spatially":[22],"connected":[23],"regions":[24,299,414,428],"homogeneous":[26],"relationships":[27],"between":[28],"variables":[29,603],"(spatial":[30,315],"regimes).":[31],"Although":[32],"various":[33],"regionalization":[34],"algorithms":[35,63,87,105,812],"have":[36,52,194,300],"been":[37,53],"proposed":[38,86],"and":[39,70,96,128,171,176,225,250,440,537,541,620,625,632,668,698,703,724,738,758,783,791,804,808,840,851,860,870],"studied":[40],"in":[41,203,258,265,276,367,449,483,524,567,577,594,734,742,747,767,857],"the":[42,75,115,134,180,201,234,270,277,292,306,310,353,384,388,392,411,420,424,445,450,456,464,472,479,496,503,506,519,530,554,578,589,595,599,611,616,679,699,719,770,786,795,816,819,829,835],"field":[43],"analytics,":[46,754],"methods":[47],"optimize":[49],"regimes":[51,238],"largely":[54,119],"unexplored.":[55],"In":[56,527],"this":[57,183,359,607],"paper,":[58,307],"we":[59,308,382],"propose":[60],"two":[61,97,377,579],"new":[62],"for":[64,159,339,588,772],"regime":[66],"delineation,":[67],"two-stage":[68,116,618],"K-Models":[69,117,582,619],"Regional-K-Models.":[71],"We":[72],"also":[73,323,548],"extend":[74],"classic":[76],"Automatic":[77],"Zoning":[78],"Procedure":[79],"a":[81,91,216,259,371,658,715,739],"context.":[84],"are":[88,168,185,246,286],"applied":[89,549],"series":[92],"synthetic":[94],"datasets":[95],"real-world":[98],"datasets.":[99],"Results":[100],"indicate":[101],"that":[102,178,192,233,264,410],"all":[103],"three":[104],"achieve":[106],"superior":[107,633],"comparable":[109,629],"performance":[110],"existing":[112,121],"approaches,":[113],"while":[114,592],"algorithm":[118,421],"outperforms":[120],"approaches":[122],"on":[123,317,645,649,657,709,868,874],"model":[124],"fitting,":[125],"region":[126,205,372,525],"reconstruction":[127],"coefficient":[129,457,522],"estimation.":[130],"Our":[131,320],"work":[132],"enriches":[133],"analytics":[136],"toolbox":[137],"explore":[139],"heterogeneous":[141],"processes.Keywords:":[142],"Regionalizationspatial":[143],"heterogeneityspatial":[144],"regimespatial":[145],"NotesAcknowledgmentsThe":[147],"authors":[148,190],"thank":[149],"members":[150],"Spatial":[152],"Analysis":[153],"Group,":[154],"Spatio-temporal":[155,692],"Social":[156],"Sensing":[157,723,839],"Lab":[158],"helpful":[160],"discussion.":[161],"constructive":[163],"comments":[164],"from":[165,240,512,678,744,785,794,854],"anonymous":[166],"reviewers":[167],"gratefully":[169],"acknowledged.Data":[170],"codes":[172,177],"availability":[173],"statementThe":[174,189],"data":[175,314,316,328],"support":[179],"findings":[181],"study":[184],"available":[186],"at":[187,718,769,834],"https://github.com/Nithouson/regreg.Disclosure":[188],"declare":[191],"they":[193],"no":[195],"conflict":[196],"interest.Notes1":[198],"For":[199],"example,":[200],"population":[202],"each":[204,251,289,528],"required":[207,425],"as":[210,212,255,365,539,561],"similar":[211,301],"possible":[213],"above":[215],"predefined":[217],"value":[218,492,520],"(see":[219],"Duque":[220],"et":[221,229,545],"al.":[222,230,546],"(Citation2012),":[223],"Folch":[224],"Spielman":[226],"(Citation2014),":[227],"Wei":[228],"(Citation2021)).2":[231],"Note":[232,263],"optimization":[235],"differs":[239],"Openshaw":[241],"(Citation1978),":[242],"where":[243,350,461],"units":[245,375,448],"aggregated":[247],"into":[248],"areas,":[249],"area":[252],"treated":[254],"an":[256,487,661],"observation":[257,327],"global":[260],"model.3":[262],"EquationEquation":[266],"1(1)":[267],"L(R)=\u2211j=1p\u22111\u2264i1<i2\u2264nI[ui1,ui2\u2208Rj]||xi1\u2212xi2||2,(1)":[268],",":[269],"number":[271,354,412,426,446,600],"unit":[274],"pairs":[275],"sum":[278],"\u2211j=1M(|Rj|2),":[280],"which":[281,386],"smaller":[283],"if":[284],"|Rj|(j=1,\u2026,M)":[285],"close":[287,347],"other.":[290],"Hence":[291],"objective":[293],"function":[294],"might":[295],"favor":[296],"solutions":[297],"whose":[298],"numbers":[302],"units.4":[304],"Throughout":[305],"describe":[309],"case":[311],"lattice":[313],"areal":[318],"units).":[319],"approach":[321],"applicable":[324],"point":[326],"after":[329,391],"building":[330],"adjacency":[331],"(with":[332],"k-nearest":[333],"neighbors":[334],"(KNN)":[335],"Delaunay":[337],"triangulation,":[338],"example).5":[340],"This":[341,432,557],"usually":[342],"happens":[343],"when":[344],"min_obs":[345,395,439,573,593],"n/p,":[349],"p":[351],"regions.":[356],"Given":[357],"min_obs\u226an/p,":[358],"issue":[360,433],"does":[361],"not":[362,565,640],"cause":[363],"problems,":[364],"observed":[366,820],"our":[368,568,646],"experiments.6":[369],"If":[370],"inadequate":[374],"has":[376],"more":[379],"neighboring":[380],"regions,":[381],"select":[383],"neighbor":[385],"minimizes":[387],"total":[389],"SSR":[390,613],"merge.7":[393],"When":[394],"too":[397,402],"large":[398],"K":[400],"small":[403],"(close":[404],"p),":[406],"exceptions":[407],"occur":[409],"less":[416],"than":[417,615],"p,":[418],"hence":[419],"cannot":[422],"produce":[423],"by":[429,437,485,676],"merging":[430],"'micro-clusters'.":[431],"can":[434,509],"solved":[436],"adjusting":[438],"K.8":[441],"Let":[442,516],"nr":[443],"denote":[444,518],"region.":[451],"OLS":[453],"estimation":[454,638],"vector":[458,474],"\u03b2=(XTX)\u22121XTy,":[460],"X":[462],"nr\u00d7(m+1)":[465],"matrix":[466],"independent":[468,488,602],"variables,":[469],"y":[470],"nr-dimensional":[473],"dependent":[476],"variable.":[477],"Here":[478,584],"intercept":[480],"included":[482],"\u03b2":[484],"adding":[486],"variable":[489],"constant":[491],"1.":[493],"By":[494],"applying":[495],"Sherman-Morrison":[497],"formula":[498],"(Bartlett":[499],"Citation1951)":[500],"update":[502],"(XTX)\u22121":[504],"term,":[505],"time":[507],"complexity":[508],"reduced":[511],"O(m2(nr+m))":[513],"O(m(nr+m)).9":[515],"\u03b2i,j":[517],"\u03b2i":[523],"Rj.":[526],"simulation,":[529],"list":[531],"(\u22122,\u22121,0,1,2)":[532],"randomly":[534],"shuffled":[535],"twice":[536],"used":[538,576,587],"(\u03b21,1,\u2026,\u03b21,5)":[540],"(\u03b22,1,\u2026,\u03b22,5),":[542],"respectively.10":[543],"Helbich":[544],"(Citation2013)":[547],"principal":[550],"component":[551],"analysis":[552],"GWR":[555,637],"coefficients.":[556],"step":[558],"skipped,":[560],"dimension":[562],"reduction":[563],"needed":[566],"experiment.11":[569],"Different":[570],"values":[571],"stages":[580],"algorithm.":[583],"min_obs=10":[585],"merge":[590],"stage,":[591],"partition":[596],"stage":[597],"plus":[604],"1":[605],"throughout":[606],"paper.12":[608],"Even":[609],"considering":[610],"average":[612],"rather":[614],"lowest,":[617],"AZP":[621],"consistently":[622],"outperform":[623],"GWR-Skater":[624],"Skater-reg;":[626],"Regional-K-Models":[627],"Skater-reg":[631],"GWR-Skater.13":[635],"did":[639],"complete":[641],"within":[642],"30":[643],"minutes":[644],"machine.14":[647],"Experiments":[648],"King":[650],"County":[651],"house":[652],"price":[653],"dataset":[654],"performed":[656],"computer":[659],"Intel":[662],"Core":[663],"i5-1135G7":[664],"CPU":[665],"(2.40":[666],"GHz)":[667],"16GB":[669],"memory.Additional":[671],"informationFundingThis":[672],"research":[673,750,864],"was":[674],"supported":[675],"grants":[677],"National":[680,700],"Natural":[681],"Science":[682,737],"Foundation":[683],"China":[685,707],"(41830645,":[686],"42271426,":[687],"41971331,":[688],"82273731),":[689],"Smart":[690],"Guangzhou":[691],"Information":[693,726,736,842],"Cloud":[694],"Platform":[695],"Construction":[696],"(GZIT2016-A5-147)":[697],"Key":[701],"Research":[702],"Development":[704],"Program":[705],"(2021YFC2701905).Notes":[708],"contributorsHao":[710],"GuoHao":[711],"Guo":[712],"currently":[714,828],"Ph.D.":[716,793,852],"candidate":[717],"Institute":[720,836],"Remote":[722,838],"Geographic":[725,735,841],"Systems,":[727,843],"Peking":[728,745,844,855],"University.":[729,845],"He":[730,779,802,846],"received":[731,780,847],"his":[732,781,792,848],"B.S.":[733,741,782],"dual":[740],"Mathematics":[743],"University":[746,787,796,856],"2020.":[748],"His":[749,863],"interests":[751,865],"include":[752],"geo-spatial":[755],"artificial":[756],"intelligence":[757],"optimization.Andre":[760],"PythonAndre":[761],"Python":[762],"ZJU100":[764],"Young":[765],"Professor":[766,831],"Statistics":[768],"Center":[771],"Data":[773],"Science,":[774],"Zhejiang":[775],"University,":[776],"P.R.":[777],"China.":[778],"M.S.":[784,850],"Fribourg,":[789],"Switzerland,":[790],"St":[798],"Andrews,":[799],"United":[800],"Kingdom.":[801],"develops":[803],"applies":[805],"models":[807],"interpretable":[809],"machine":[810],"learning":[811],"better":[814],"understand":[815],"mechanisms":[817],"behind":[818],"patterns":[821],"phenomena.Yu":[824],"LiuYu":[825],"Liu":[826],"Boya":[830],"GIScience":[833],"B.S.,":[849],"degrees":[853],"1994,":[858],"1997":[859],"2003,":[861],"respectively.":[862],"mainly":[866],"focus":[867],"humanities":[869],"social":[871],"sciences":[872],"based":[873],"big":[875],"geo-data.":[876]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
