{"id":"https://openalex.org/W4409785440","doi":"https://doi.org/10.1177/14727978251337993","title":"Crime forecasting: A spatio-temporal analysis with deep learning models","display_name":"Crime forecasting: A spatio-temporal analysis with deep learning models","publication_year":2025,"publication_date":"2025-04-25","ids":{"openalex":"https://openalex.org/W4409785440","doi":"https://doi.org/10.1177/14727978251337993"},"language":"en","primary_location":{"id":"doi:10.1177/14727978251337993","is_oa":false,"landing_page_url":"https://doi.org/10.1177/14727978251337993","pdf_url":null,"source":{"id":"https://openalex.org/S2765058733","display_name":"Journal of Computational Methods in Sciences and Engineering","issn_l":"1472-7978","issn":["1472-7978","1875-8983"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational Methods in Sciences and Engineering","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":null,"display_name":"Li Mao","orcid":"https://orcid.org/0000-0002-7993-5276"},"institutions":[{"id":"https://openalex.org/I4210147983","display_name":"Guangdong Police College","ror":"https://ror.org/05krxyw16","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210147983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Mao","raw_affiliation_strings":["Cyber Security College, Guangdong Police College, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-7993-5276","affiliations":[{"raw_affiliation_string":"Cyber Security College, Guangdong Police College, Guangzhou, China","institution_ids":["https://openalex.org/I4210147983"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wei Du","orcid":"https://orcid.org/0009-0005-8129-2694"},"institutions":[{"id":"https://openalex.org/I4210147983","display_name":"Guangdong Police College","ror":"https://ror.org/05krxyw16","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210147983"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Du","raw_affiliation_strings":["Cyber Security College, Guangdong Police College, Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0005-8129-2694","affiliations":[{"raw_affiliation_string":"Cyber Security College, Guangdong Police College, Guangzhou, China","institution_ids":["https://openalex.org/I4210147983"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shuo Wen","orcid":"https://orcid.org/0009-0006-6758-9421"},"institutions":[{"id":"https://openalex.org/I4210147983","display_name":"Guangdong Police College","ror":"https://ror.org/05krxyw16","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210147983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuo Wen","raw_affiliation_strings":["Cyber Security College, Guangdong Police College, Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0006-6758-9421","affiliations":[{"raw_affiliation_string":"Cyber Security College, Guangdong Police College, Guangzhou, China","institution_ids":["https://openalex.org/I4210147983"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Qi Li","orcid":"https://orcid.org/0009-0002-0202-4797"},"institutions":[{"id":"https://openalex.org/I4210147983","display_name":"Guangdong Police College","ror":"https://ror.org/05krxyw16","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210147983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Li","raw_affiliation_strings":["Cyber Security College, Guangdong Police College, Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0002-0202-4797","affiliations":[{"raw_affiliation_string":"Cyber Security College, Guangdong Police College, Guangzhou, China","institution_ids":["https://openalex.org/I4210147983"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tong Zhang","orcid":"https://orcid.org/0009-0003-5104-3465"},"institutions":[{"id":"https://openalex.org/I4210147983","display_name":"Guangdong Police College","ror":"https://ror.org/05krxyw16","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210147983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Zhang","raw_affiliation_strings":["Cyber Security College, Guangdong Police College, Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0003-5104-3465","affiliations":[{"raw_affiliation_string":"Cyber Security College, Guangdong Police College, Guangzhou, China","institution_ids":["https://openalex.org/I4210147983"]}]},{"author_position":"last","author":{"id":null,"display_name":"Wei Zhong","orcid":"https://orcid.org/0009-0001-7758-8709"},"institutions":[{"id":"https://openalex.org/I4210147983","display_name":"Guangdong Police College","ror":"https://ror.org/05krxyw16","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210147983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zhong","raw_affiliation_strings":["Cyber Security College, Guangdong Police College, Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0001-7758-8709","affiliations":[{"raw_affiliation_string":"Cyber Security College, Guangdong Police College, Guangzhou, China","institution_ids":["https://openalex.org/I4210147983"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210147983"],"apc_list":null,"apc_paid":null,"fwci":12.8313,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.98273236,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"25","issue":"5","first_page":"4090","last_page":"4099"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10574","display_name":"Crime Patterns and Interventions","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10574","display_name":"Crime Patterns and Interventions","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9846000075340271,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9682000279426575,"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/computer-science","display_name":"Computer science","score":0.8097073435783386},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.7511165142059326},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.65264493227005},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6154230833053589},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6018661856651306},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5511811971664429},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.537990391254425},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48458683490753174},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.464969664812088},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4602014720439911},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.44574227929115295}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8097073435783386},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.7511165142059326},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.65264493227005},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6154230833053589},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6018661856651306},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5511811971664429},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.537990391254425},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48458683490753174},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.464969664812088},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4602014720439911},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.44574227929115295},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1177/14727978251337993","is_oa":false,"landing_page_url":"https://doi.org/10.1177/14727978251337993","pdf_url":null,"source":{"id":"https://openalex.org/S2765058733","display_name":"Journal of Computational Methods in Sciences and Engineering","issn_l":"1472-7978","issn":["1472-7978","1875-8983"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational Methods in Sciences and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7400000095367432,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W2039617089","https://openalex.org/W2064675550","https://openalex.org/W2068612075","https://openalex.org/W3084405808","https://openalex.org/W3127538025","https://openalex.org/W3147992976","https://openalex.org/W3158174949","https://openalex.org/W4205832669","https://openalex.org/W4206323677","https://openalex.org/W4220732194","https://openalex.org/W4237638342","https://openalex.org/W4243514854","https://openalex.org/W4247324276","https://openalex.org/W4285264426","https://openalex.org/W4385750124","https://openalex.org/W4386232616","https://openalex.org/W4388851184","https://openalex.org/W4399360946","https://openalex.org/W4400490407","https://openalex.org/W4400533311","https://openalex.org/W4403798602","https://openalex.org/W4405440071","https://openalex.org/W4406983200"],"related_works":["https://openalex.org/W2931688134","https://openalex.org/W2377919138","https://openalex.org/W2378857091","https://openalex.org/W103652678","https://openalex.org/W4226090359","https://openalex.org/W2059697060","https://openalex.org/W936373746","https://openalex.org/W2975817033","https://openalex.org/W4256502920","https://openalex.org/W4382701072"],"abstract_inverted_index":{"This":[0],"study":[1],"uses":[2],"deep-learning":[3],"models":[4],"to":[5,47,76,156],"predict":[6],"city":[7],"partition":[8],"crime":[9,27,52,102,131],"counts":[10],"on":[11,89],"specific":[12],"days.":[13],"It":[14],"helps":[15],"police":[16],"enhance":[17,143],"surveillance,":[18],"gather":[19],"intelligence,":[20],"and":[21,39,65,86,172],"proactively":[22],"prevent":[23],"crimes.":[24],"We":[25,71],"formulate":[26],"count":[28],"prediction":[29,40,91,110],"as":[30],"a":[31,56,73],"spatiotemporal":[32,43],"sequence":[33],"challenge,":[34],"where":[35],"both":[36],"input":[37],"data":[38,82,103,132,170,175],"targets":[41],"are":[42],"sequences.":[44],"In":[45],"order":[46],"improve":[48],"the":[49,78,90,105,113,123],"accuracy":[50],"of":[51,80,93],"forecasting,":[53],"we":[54],"introduce":[55],"new":[57],"model":[58,107,114,126,145],"that":[59,122],"combines":[60],"Convolutional":[61],"Neural":[62],"Networks":[63],"(CNN)":[64],"Long":[66],"Short-Term":[67],"Memory":[68],"(LSTM)":[69],"networks.":[70],"conducted":[72],"comparative":[74],"analysis":[75],"access":[77],"effects":[79],"various":[81],"sequences,":[83],"including":[84],"raw":[85,101,174],"binned":[87],"data,":[88],"errors":[92],"four":[94],"deep":[95],"learning":[96],"forecasting":[97,106,144],"models.":[98],"Directly":[99],"inputting":[100],"into":[104,135,158,162],"causes":[108],"high":[109],"errors,":[111],"making":[112],"unsuitable":[115],"for":[116],"real-world":[117],"use.":[118],"The":[119],"findings":[120],"indicate":[121],"proposed":[124],"CNN-LSTM":[125],"achieves":[127],"optimal":[128,167],"performance":[129],"when":[130],"is":[133],"categorized":[134],"10":[136,163],"or":[137],"5":[138],"groups.":[139],"Data":[140],"binning":[141,161],"can":[142],"performance,":[146],"but":[147],"poorly":[148],"defined":[149],"intervals":[150,164],"may":[151],"reduce":[152],"map":[153],"granularity.":[154],"Compared":[155],"dividing":[157],"five":[159],"bins,":[160],"strikes":[165],"an":[166],"balance,":[168],"preserving":[169],"characteristics":[171],"surpassing":[173],"in":[176],"predictive":[177],"modeling":[178],"efficacy.":[179]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}