{"id":"https://openalex.org/W4417335712","doi":"https://doi.org/10.1145/3764919.3770879","title":"Optimization of Beef Noodle Shop Layout in Lanzhou City Based on Accessibility Analysis","display_name":"Optimization of Beef Noodle Shop Layout in Lanzhou City Based on Accessibility Analysis","publication_year":2025,"publication_date":"2025-11-03","ids":{"openalex":"https://openalex.org/W4417335712","doi":"https://doi.org/10.1145/3764919.3770879"},"language":null,"primary_location":{"id":"doi:10.1145/3764919.3770879","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3764919.3770879","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3764919.3770879","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th ACM SIGSPATIAL International Workshop on Spatial Big Data and AI for Industrial Applications","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3764919.3770879","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120806870","display_name":"Xiaoxiao Guo","orcid":"https://orcid.org/0009-0009-1041-7751"},"institutions":[{"id":"https://openalex.org/I3133134087","display_name":"Lanzhou Jiaotong University","ror":"https://ror.org/03144pv92","country_code":"CN","type":"education","lineage":["https://openalex.org/I3133134087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoxiao Guo","raw_affiliation_strings":["Faculty of Geomatics,Lanzhou Jiaotong University,Lanzhou 730070, China, Lanzhou, China"],"raw_orcid":"https://orcid.org/0009-0009-1041-7751","affiliations":[{"raw_affiliation_string":"Faculty of Geomatics,Lanzhou Jiaotong University,Lanzhou 730070, China, Lanzhou, China","institution_ids":["https://openalex.org/I3133134087"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100456654","display_name":"Shaohua Wang","orcid":"https://orcid.org/0000-0001-8651-9505"},"institutions":[{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaohua Wang","raw_affiliation_strings":["Aerospace Information Research Institute,CAS,Beijing 10094,China, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8651-9505","affiliations":[{"raw_affiliation_string":"Aerospace Information Research Institute,CAS,Beijing 10094,China, Beijing, China","institution_ids":["https://openalex.org/I4210137199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028790646","display_name":"Wenda Wang","orcid":"https://orcid.org/0009-0003-4593-4819"},"institutions":[{"id":"https://openalex.org/I3133134087","display_name":"Lanzhou Jiaotong University","ror":"https://ror.org/03144pv92","country_code":"CN","type":"education","lineage":["https://openalex.org/I3133134087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenda Wang","raw_affiliation_strings":["Faculty of Geomatics,Lanzhou Jiaotong University,Lanzhou 730070, China, Lanzhou, China"],"raw_orcid":"https://orcid.org/0009-0003-4593-4819","affiliations":[{"raw_affiliation_string":"Faculty of Geomatics,Lanzhou Jiaotong University,Lanzhou 730070, China, Lanzhou, China","institution_ids":["https://openalex.org/I3133134087"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hao Wang","orcid":"https://orcid.org/0009-0001-8406-5148"},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Wang","raw_affiliation_strings":["Henan Key Laboratory of Big Data Analysis and Processing,Henan University,Kaifeng 475004, China, Kaifeng, China"],"raw_orcid":"https://orcid.org/0009-0001-8406-5148","affiliations":[{"raw_affiliation_string":"Henan Key Laboratory of Big Data Analysis and Processing,Henan University,Kaifeng 475004, China, Kaifeng, China","institution_ids":["https://openalex.org/I173899330"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100317226","display_name":"Chang Liu","orcid":"https://orcid.org/0009-0000-8623-2248"},"institutions":[{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chang Liu","raw_affiliation_strings":["Aerospace Information Research Institute, CAS, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0000-8623-2248","affiliations":[{"raw_affiliation_string":"Aerospace Information Research Institute, CAS, Beijing, China","institution_ids":["https://openalex.org/I4210137199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102951145","display_name":"Jingyi Zhou","orcid":"https://orcid.org/0000-0002-0119-3583"},"institutions":[{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyi Zhou","raw_affiliation_strings":["Aerospace Information Research Institute, CAS, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0119-3583","affiliations":[{"raw_affiliation_string":"Aerospace Information Research Institute, CAS, Beijing, China","institution_ids":["https://openalex.org/I4210137199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"56","last_page":"63"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12306","display_name":"Urban and Freight Transport Logistics","score":0.515500009059906,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T12306","display_name":"Urban and Freight Transport Logistics","score":0.515500009059906,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T10298","display_name":"Urban Transport and Accessibility","score":0.29019999504089355,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11536","display_name":"Consumer Retail Behavior Studies","score":0.01769999973475933,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.5735999941825867},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.4359999895095825},{"id":"https://openalex.org/keywords/truck","display_name":"Truck","score":0.4065999984741211},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.3831999897956848},{"id":"https://openalex.org/keywords/mode","display_name":"Mode (computer interface)","score":0.36010000109672546},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.3370000123977661}],"concepts":[{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.5735999941825867},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.5228999853134155},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.4359999895095825},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.41269999742507935},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4081000089645386},{"id":"https://openalex.org/C52121051","wikidata":"https://www.wikidata.org/wiki/Q43193","display_name":"Truck","level":2,"score":0.4065999984741211},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3831999897956848},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.36010000109672546},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.3370000123977661},{"id":"https://openalex.org/C154611951","wikidata":"https://www.wikidata.org/wiki/Q393233","display_name":"Urban agglomeration","level":2,"score":0.3264999985694885},{"id":"https://openalex.org/C2779214396","wikidata":"https://www.wikidata.org/wiki/Q8560502","display_name":"Trip distribution","level":2,"score":0.31779998540878296},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3149000108242035},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.26930001378059387},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25380000472068787},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.25380000472068787},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.2533999979496002}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3764919.3770879","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3764919.3770879","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3764919.3770879","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th ACM SIGSPATIAL International Workshop on Spatial Big Data and AI for Industrial Applications","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3764919.3770879","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3764919.3770879","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3764919.3770879","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 4th ACM SIGSPATIAL International Workshop on Spatial Big Data and AI for Industrial Applications","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1758018836","display_name":null,"funder_award_id":"E2Z105010F","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"},{"id":"https://openalex.org/G1801965831","display_name":null,"funder_award_id":"E43302020D","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"},{"id":"https://openalex.org/G7080773451","display_name":null,"funder_award_id":"42471495","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/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4417335712.pdf","grobid_xml":"https://content.openalex.org/works/W4417335712.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W1981934262","https://openalex.org/W1987102421","https://openalex.org/W1998319082","https://openalex.org/W2011658408","https://openalex.org/W2123700529","https://openalex.org/W2186961306","https://openalex.org/W2211015082","https://openalex.org/W2407665818","https://openalex.org/W2485132131","https://openalex.org/W2507414086","https://openalex.org/W2771379496","https://openalex.org/W2807569932","https://openalex.org/W2944160886","https://openalex.org/W3007489912","https://openalex.org/W3032597294","https://openalex.org/W3120166401","https://openalex.org/W3159935990","https://openalex.org/W4280561899","https://openalex.org/W4306412518","https://openalex.org/W4310018452","https://openalex.org/W4389080110"],"related_works":[],"abstract_inverted_index":{"This":[0],"study":[1],"employs":[2],"kernel":[3],"density":[4,17],"estimation,":[5],"geographically":[6],"weighted":[7],"methods,":[8],"and":[9,18,28,61,72,84,94,113,119,127,156,163],"Gaussian":[10,98],"distance":[11],"modeling,":[12],"in":[13,36,49,109,117],"conjunction":[14],"with":[15,56,68],"population":[16],"traffic":[19],"network":[20],"datasets,":[21],"to":[22,141],"investigate":[23],"the":[24,97,110,128,150],"spatial":[25],"distribution":[26],"characteristics":[27],"service":[29],"accessibility":[30,108,116,143],"of":[31,87,153],"Lanzhou-style":[32],"beef":[33],"noodle":[34],"shops":[35,45,155],"Lanzhou's":[37],"main":[38],"urban":[39,111,160],"area.":[40],"Results":[41],"demonstrate":[42],"that":[43],"these":[44],"are":[46,139],"highly":[47],"concentrated":[48],"core":[50],"districts":[51],"(Chengguan,":[52],"Anning,":[53],"Xigu,":[54],"Qilihe)":[55],"statistically":[57],"significant":[58],"agglomeration":[59],"effects,":[60],"their":[62],"clustered":[63],"zones":[64],"exhibit":[65],"good":[66],"integration":[67],"major":[69],"road":[70],"networks":[71],"residential":[73],"areas.":[74,121],"Entropy":[75],"weight":[76],"analysis":[77,126],"reveals":[78],"robust":[79],"correlations":[80],"between":[81],"shop":[82,137],"locations":[83],"key":[85],"points":[86],"interest":[88],"(POIs),":[89],"including":[90],"hotels,":[91],"commercial":[92,161],"complexes,":[93],"transportation":[95],"hubs;":[96],"Two-Step":[99],"Floating":[100],"Catchment":[101],"Area":[102],"(G2SFCA)":[103],"method":[104],"indicates":[105],"notably":[106],"higher":[107],"center":[112],"markedly":[114],"lower":[115],"fringe":[118],"mountainous":[120],"By":[122],"integrating":[123],"buffer":[124],"zone":[125],"Maximum":[129],"Coverage":[130],"Location":[131],"Problem":[132],"(MCLP)":[133],"model,":[134],"seven":[135],"new":[136],"sites":[138],"proposed":[140],"address":[142],"gaps,":[144],"providing":[145],"a":[146],"scientific":[147],"basis":[148],"for":[149,159],"rational":[151],"layout":[152],"such":[154],"offering":[157],"references":[158],"optimization":[162],"cultural":[164],"heritage":[165],"safeguarding.":[166]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-12-15T00:00:00"}