{"id":"https://openalex.org/W3181847344","doi":"https://doi.org/10.1108/ijwis-04-2021-0045","title":"Simulation of crowd management using deep learning algorithm","display_name":"Simulation of crowd management using deep learning algorithm","publication_year":2021,"publication_date":"2021-07-07","ids":{"openalex":"https://openalex.org/W3181847344","doi":"https://doi.org/10.1108/ijwis-04-2021-0045","mag":"3181847344"},"language":"en","primary_location":{"id":"doi:10.1108/ijwis-04-2021-0045","is_oa":false,"landing_page_url":"https://doi.org/10.1108/ijwis-04-2021-0045","pdf_url":null,"source":{"id":"https://openalex.org/S145159096","display_name":"International Journal of Web Information Systems","issn_l":"1744-0084","issn":["1744-0084","1744-0092"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Web Information Systems","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/A5043627508","display_name":"Ibtehal Nafea","orcid":null},"institutions":[{"id":"https://openalex.org/I23075662","display_name":"Taibah University","ror":"https://ror.org/01xv1nn60","country_code":"SA","type":"education","lineage":["https://openalex.org/I23075662"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Ibtehal Talal Nafea","raw_affiliation_strings":["Computer Science and Engineering College, Taibah University, Medina, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering College, Taibah University, Medina, Saudi Arabia","institution_ids":["https://openalex.org/I23075662"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5043627508"],"corresponding_institution_ids":["https://openalex.org/I23075662"],"apc_list":null,"apc_paid":null,"fwci":0.9684,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.71703131,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"17","issue":"4","first_page":"321","last_page":"332"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9954000115394592,"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/T13853","display_name":"Teacher Education and Assessments","score":0.9865000247955322,"subfield":{"id":"https://openalex.org/subfields/3304","display_name":"Education"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hajj","display_name":"Hajj","score":0.8409675359725952},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8173788189888},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6584537029266357},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5408539772033691},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5139521956443787},{"id":"https://openalex.org/keywords/section","display_name":"Section (typography)","score":0.5115002393722534},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4763650894165039},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4681549072265625},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4295518398284912},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4235171675682068},{"id":"https://openalex.org/keywords/pilgrimage","display_name":"Pilgrimage","score":0.4115403890609741},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37668269872665405}],"concepts":[{"id":"https://openalex.org/C2781009399","wikidata":"https://www.wikidata.org/wiki/Q234915","display_name":"Hajj","level":3,"score":0.8409675359725952},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8173788189888},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6584537029266357},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5408539772033691},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5139521956443787},{"id":"https://openalex.org/C2780129039","wikidata":"https://www.wikidata.org/wiki/Q1931107","display_name":"Section (typography)","level":2,"score":0.5115002393722534},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4763650894165039},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4681549072265625},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4295518398284912},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4235171675682068},{"id":"https://openalex.org/C2779448473","wikidata":"https://www.wikidata.org/wiki/Q1644573","display_name":"Pilgrimage","level":2,"score":0.4115403890609741},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37668269872665405},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C27206212","wikidata":"https://www.wikidata.org/wiki/Q34178","display_name":"Theology","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C195244886","wikidata":"https://www.wikidata.org/wiki/Q41493","display_name":"Ancient history","level":1,"score":0.0},{"id":"https://openalex.org/C4445939","wikidata":"https://www.wikidata.org/wiki/Q432","display_name":"Islam","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1108/ijwis-04-2021-0045","is_oa":false,"landing_page_url":"https://doi.org/10.1108/ijwis-04-2021-0045","pdf_url":null,"source":{"id":"https://openalex.org/S145159096","display_name":"International Journal of Web Information Systems","issn_l":"1744-0084","issn":["1744-0084","1744-0092"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Web Information Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1873971133","https://openalex.org/W1979852252","https://openalex.org/W1985310176","https://openalex.org/W2073093975","https://openalex.org/W2073131864","https://openalex.org/W2155371606","https://openalex.org/W2521185566","https://openalex.org/W2567714070","https://openalex.org/W2593042479","https://openalex.org/W2785715739","https://openalex.org/W2905383564","https://openalex.org/W2989162561"],"related_works":["https://openalex.org/W3107179269","https://openalex.org/W297345137","https://openalex.org/W1592675040","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3103566983","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Purpose":[0],"This":[1,199,329,354,492,536,563],"study":[2,59,225,330,537],"aims":[3],"to":[4,39,66,278,308,314,325,347,365,403,414,440,516,542,547,554,567,651,657,683,738],"propose":[5],"a":[6,11,222,253,322,332,343,370,495,514,540,606,623,639,673,699],"new":[7],"simulation":[8,176,215],"approach":[9,65,147],"for":[10,334,735],"real-life":[12,223],"large":[13],"and":[14,34,91,105,160,166,175,183,212,216,342,374,395,430,472,521,532,647,671,704,719,740],"complex":[15],"crowd":[16,32,42,51,71,90,206,237,317,335,420,578,595,604,697],"management":[17,207,336,579],"which":[18,57,191,251,368,449,528,611,731],"takes":[19,84],"into":[20,94,421],"account":[21],"deep":[22,62,217,371],"learning":[23,63,372],"algorithm.":[24],"Moreover,":[25],"the":[26,31,41,48,54,58,61,68,74,85,88,108,123,126,139,145,163,202,210,264,270,273,285,289,316,360,378,381,387,396,405,419,447,455,460,467,479,486,510,519,544,550,568,593,603,613,627,634,653,666,679,688,693,696,706,725,736],"proposed":[27,146,331,355,539,715],"model":[28,49,76,333,406,541,583,621,716],"also":[29,35],"determines":[30],"level":[33,551,608,694],"sends":[36],"an":[37,297,504,590],"alarm":[38,346,591],"avoid":[40,326,555],"from":[43,267,558],"exceeding":[44],"its":[45,451,644],"limit.":[46],"Also,":[47],"estimates":[50],"density":[52],"in":[53,155,180,229,288,300,321,389,417,443,577,638,698,711],"pictures":[55],"through":[56],"evaluates":[60],"algorithm":[64,154,480],"address":[67],"problem":[69,545],"of":[70,78,87,112,118,125,128,195,204,214,226,236,256,263,276,284,291,345,350,380,392,398,445,458,506,524,549,552,561,602,629,636,655,668,695],"congestion.":[72],"Furthermore,":[73],"suggested":[75,682],"comprises":[77,111],"two":[79],"main":[80],"components.":[81],"The":[82,116,130,400,432,582,620,661,714],"first":[83,456,461],"images":[86],"moving":[89],"classifies":[92],"them":[93],"five":[95,422],"categories":[96,423],"such":[97,586],"as":[98,134,168,170,384,386,437,497,513,585,722],"\u201cheavily":[99],"crowded,":[100,101,425,427],"semi-crowded,":[102,428],"light":[103,625,631,663,690,729],"crowded":[104],"normal,\u201d":[106],"whereas":[107],"second":[109,487],"one":[110,283],"colour":[113,117],"warnings":[114],"(five).":[115],"these":[119],"lights":[120],"depends":[121,358],"upon":[122],"results":[124,174,433,502],"process":[127],"classification.":[129],"paper":[131,187,200],"is":[132,192,252,282,296,312,369,402,469,481,494,526,529,702,717],"structured":[133],"follows.":[135],"Section":[136,142,156,193],"2":[137],"describes":[138],"theoretical":[140],"background;":[141],"3":[143],"suggests":[144],"followed":[148],"by":[149,208,338,484],"convolutional":[150,462],"neural":[151],"network":[152],"(CNN)":[153],"4.":[157],"Sections":[158,181],"5":[159],"6":[161],"explain":[162],"data":[164,362],"set":[165,363],"parameters":[167],"well":[169,385],"modelling":[171],"network.":[172],"Experiment,":[173],"evaluation":[177],"are":[178,572,609,681],"explained":[179],"7":[182],"8.":[184],"Finally,":[185,687],"this":[186,196,599],"ends":[188],"with":[189,245,407,464,489,503],"conclusion":[190],"9":[194],"paper.":[197],"Design/methodology/approach":[198],"addresses":[201],"issue":[203],"large-scale":[205],"exploiting":[209],"techniques":[211],"algorithms":[213],"learning.":[218],"It":[219,311],"focuses":[220],"on":[221,359],"case":[224],"Hajj":[227,239,292],"pilgrimage":[228,240],"Saudi":[230],"Arabia":[231],"that":[232,247,281,571,587,616,633,658,665,692,705,712],"exhibits":[233],"intricate":[234],"pattern":[235],"management.":[238],"includes":[241],"performing":[242,318],"Umrah":[243],"along":[244],"hajj":[246],"involves":[248],"several":[249],"steps":[250],"sacred":[254],"prayer":[255],"Muslims":[257,266],"performed":[258],"at":[259,475],"different":[260],"time":[261],"span":[262],"year.":[265],"all":[268,303],"over":[269],"world":[271],"visit":[272],"holy":[274],"city":[275],"Mecca":[277],"perform":[279,309],"Tawaf":[280,319],"stages":[286],"included":[287],"performance":[290],"or":[293],"Umrah,":[294],"it":[295,412,498,588,649,723,733],"obligatory":[298],"step":[299],"prayer.":[301],"Accordingly,":[302],"pilgrims":[304,448,637,669,680,707,737],"require":[305],"visiting":[306],"Mataf":[307],"Tawaf.":[310,581],"essential":[313],"control":[315],"systematically":[320],"constrained":[323],"place":[324],"any":[327,556],"mishap.":[328],"system":[337,344,356,730],"using":[339,509],"image":[340,393,409],"classification":[341,394],"manage":[348],"millions":[349],"people":[351,656],"during":[352,574,580],"Hajj.":[353],"highly":[357],"adequate":[361,435],"used":[364,416,573],"train":[366,404],"CNN":[367],"technique":[373],"has":[375,538,622,642,676],"recently":[376],"drawn":[377],"attention":[379],"research":[382],"community":[383],"industry":[388],"changing":[390],"applications":[391],"recognition":[397],"speed.":[399],"purpose":[401],"mapped":[408],"data,":[410],"making":[411],"available":[413],"be":[415,441,565],"classifying":[418],"like":[424],"heavily":[426],"normal":[429],"light-crowded.":[431],"produce":[434],"signals":[436],"they":[438],"prove":[439],"helpful":[442],"terms":[444],"monitoring":[446,569],"shows":[450,691],"usefulness.":[452],"Findings":[453],"After":[454,508],"attempt":[457,493],"adding":[459,485],"layer":[463,488],"32":[465],"filters,":[466],"accuracy":[468,505,523],"not":[470],"good":[471],"stands":[473],"out":[474],"about":[476],"55%.":[477],"Therefore,":[478],"further":[482],"improved":[483,501],"64":[490],"filters.":[491],"success":[496],"gives":[499],"more":[500],"97%.":[507],"dropout":[511],"fraction":[512],"0.5":[515],"prevent":[517],"overfitting,":[518],"test":[520],"training":[522,531],"98%":[525],"achieved":[527],"acceptable":[530],"testing":[533],"accuracy.":[534],"Originality/value":[535],"solve":[543],"related":[546],"estimation":[548],"congestion":[553],"accidents":[557,615],"happening":[559],"because":[560],"it.":[562],"can":[564,708],"applied":[566],"schemes":[570],"Hajj,":[575],"especially":[576],"works":[584],"activates":[589],"when":[592],"default":[594,645],"limit":[596,646],"exceeds.":[597],"In":[598],"way,":[600],"chances":[601],"reaching":[605],"dangerous":[607],"reduced":[610],"minimizes":[612],"potential":[614],"might":[617],"take":[618],"place.":[619],"traffic":[624,728],"system,":[626],"appearance":[628],"red":[630],"means":[632],"number":[635,667],"particular":[640,659,674,700],"area":[641,675,701],"exceeded":[643],"then":[648,678],"alerts":[650],"stop":[652],"migration":[654],"area.":[660,713],"yellow":[662],"indicates":[664],"entering":[670],"leaving":[672],"equalized,":[677],"slower":[684],"their":[685],"pace.":[686],"green":[689],"low":[703],"move":[709],"freely":[710],"simple":[718],"user":[720],"friendly":[721],"uses":[724],"most":[726],"common":[727],"makes":[732],"easier":[734],"understand":[739],"follow":[741],"accordingly.":[742]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-08-13T07:04:57.449891","created_date":"2025-10-10T00:00:00"}
