{"id":"https://openalex.org/W2935976283","doi":"https://doi.org/10.1145/3314545.3314550","title":"The Application of Time Series Method in Predicting the Number of Urban Management Cases","display_name":"The Application of Time Series Method in Predicting the Number of Urban Management Cases","publication_year":2019,"publication_date":"2019-03-14","ids":{"openalex":"https://openalex.org/W2935976283","doi":"https://doi.org/10.1145/3314545.3314550","mag":"2935976283"},"language":"en","primary_location":{"id":"doi:10.1145/3314545.3314550","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3314545.3314550","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 3rd International Conference on Compute and Data Analysis","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/A5033624629","display_name":"Xiangyu Kong","orcid":"https://orcid.org/0000-0003-2084-7826"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiangyu Kong","raw_affiliation_strings":["School of Management &amp; Engineering, Nanjing University, Nanjing, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"School of Management &amp; Engineering, Nanjing University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043142189","display_name":"Fan Liu","orcid":"https://orcid.org/0000-0002-4703-4123"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Liu","raw_affiliation_strings":["School of Management &amp; Engineering, Nanjing University, Nanjing, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"School of Management &amp; Engineering, Nanjing University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101495370","display_name":"Dali Chen","orcid":"https://orcid.org/0000-0002-3075-4028"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dali Chen","raw_affiliation_strings":["School of Management &amp; Engineering, Nanjing University, Nanjing, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"School of Management &amp; Engineering, Nanjing University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5033624629"],"corresponding_institution_ids":["https://openalex.org/I881766915"],"apc_list":null,"apc_paid":null,"fwci":0.2062,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.5681167,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"84","last_page":"87"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9581000208854675,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9581000208854675,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.9498999714851379,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9452000260353088,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.7469052076339722},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6121808290481567},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5714478492736816},{"id":"https://openalex.org/keywords/taylor-series","display_name":"Taylor series","score":0.5459482073783875},{"id":"https://openalex.org/keywords/seasonality","display_name":"Seasonality","score":0.485419362783432},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3481692671775818},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24093449115753174},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1468905508518219},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.05518472194671631}],"concepts":[{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.7469052076339722},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6121808290481567},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5714478492736816},{"id":"https://openalex.org/C158946198","wikidata":"https://www.wikidata.org/wiki/Q131187","display_name":"Taylor series","level":2,"score":0.5459482073783875},{"id":"https://openalex.org/C125403950","wikidata":"https://www.wikidata.org/wiki/Q2111082","display_name":"Seasonality","level":2,"score":0.485419362783432},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3481692671775818},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24093449115753174},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1468905508518219},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.05518472194671631},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3314545.3314550","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3314545.3314550","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 3rd International Conference on Compute and Data Analysis","raw_type":"proceedings-article"},{"id":"mag:3161037468","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002269389609780","pdf_url":null,"source":{"id":"https://openalex.org/S4306500161","display_name":"ACM Proceedings","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":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"ACM Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8600000143051147,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2119996119","https://openalex.org/W2156636680","https://openalex.org/W2166488799","https://openalex.org/W2312135248","https://openalex.org/W4241115065"],"related_works":["https://openalex.org/W2125395284","https://openalex.org/W202945371","https://openalex.org/W2616486534","https://openalex.org/W4282936821","https://openalex.org/W2014145616","https://openalex.org/W3023070983","https://openalex.org/W4401950215","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"The":[0],"purpose":[1],"of":[2,10,24,36,40],"this":[3],"study":[4],"is":[5],"to":[6,18,32],"forecast":[7],"the":[8,20,29,34,37,54,59,67],"number":[9],"cases":[11],"for":[12],"urban":[13,25],"management":[14],"officers,":[15],"so":[16],"as":[17],"improve":[19],"efficiency":[21],"and":[22,47,58],"effectiveness":[23],"management.":[26],"We":[27],"extend":[28],"Holt-Winter":[30],"method":[31,57],"accommodate":[33],"pattern":[35],"time":[38],"series":[39,43],"cases.":[41],"Such":[42],"shows":[44],"two":[45],"seasonality":[46],"abnormal":[48],"increases":[49],"or":[50],"decreases.":[51],"Compared":[52],"with":[53],"traditional":[55],"Holt-Winters":[56],"one":[60,70],"improved":[61],"by":[62],"Taylor,":[63],"our":[64],"model":[65],"performs":[66],"best":[68],"in":[69],"numerical":[71],"experiment.":[72]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
