{"id":"https://openalex.org/W4321108823","doi":"https://doi.org/10.1142/s0218001422520309","title":"AACO: Aquila Anti-Coronavirus Optimization-Based Deep LSTM Network for Road Accident and Severity Detection","display_name":"AACO: Aquila Anti-Coronavirus Optimization-Based Deep LSTM Network for Road Accident and Severity Detection","publication_year":2023,"publication_date":"2023-02-16","ids":{"openalex":"https://openalex.org/W4321108823","doi":"https://doi.org/10.1142/s0218001422520309"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001422520309","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001422520309","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","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/A5024722723","display_name":"Pendela Kanchanamala","orcid":"https://orcid.org/0000-0001-6833-1365"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Pendela Kanchanamala","raw_affiliation_strings":["Department of Information Technology, GMR Institute of Technology, Rajam, Vizianagaram District 532127, Andhra Pradesh, India"],"affiliations":[{"raw_affiliation_string":"Department of Information Technology, GMR Institute of Technology, Rajam, Vizianagaram District 532127, Andhra Pradesh, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016313956","display_name":"Ramanathan Lakshmanan","orcid":"https://orcid.org/0000-0002-1532-5495"},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ramanathan Lakshmanan","raw_affiliation_strings":["School of Computer Science and Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India","institution_ids":["https://openalex.org/I876193797"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000725389","display_name":"B. Muthu Kumar","orcid":null},"institutions":[{"id":"https://openalex.org/I83737708","display_name":"REVA University","ror":"https://ror.org/03gtcxd54","country_code":"IN","type":"education","lineage":["https://openalex.org/I83737708"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"B. Muthu Kumar","raw_affiliation_strings":["School of Computing and Information Technology, REVA University, Yelahanka, Bengaluru 560064 Karnataka, India"],"affiliations":[{"raw_affiliation_string":"School of Computing and Information Technology, REVA University, Yelahanka, Bengaluru 560064 Karnataka, India","institution_ids":["https://openalex.org/I83737708"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083797053","display_name":"Balajee Maram","orcid":"https://orcid.org/0000-0001-5635-5642"},"institutions":[{"id":"https://openalex.org/I101407740","display_name":"Chandigarh University","ror":"https://ror.org/05t4pvx35","country_code":"IN","type":"education","lineage":["https://openalex.org/I101407740"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Balajee Maram","raw_affiliation_strings":["AIT-Computer Science and Engineering, University Centre for Research and Development, Chandigarh University, Mohali, India"],"affiliations":[{"raw_affiliation_string":"AIT-Computer Science and Engineering, University Centre for Research and Development, Chandigarh University, Mohali, India","institution_ids":["https://openalex.org/I101407740"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5024722723"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6219,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.63381404,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":"37","issue":"05","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10370","display_name":"Traffic and Road Safety","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T10370","display_name":"Traffic and Road Safety","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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":0.9991000294685364,"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/T12406","display_name":"IoT and GPS-based Vehicle Safety Systems","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"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/mean-squared-error","display_name":"Mean squared error","score":0.7085553407669067},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6574879884719849},{"id":"https://openalex.org/keywords/mean-absolute-percentage-error","display_name":"Mean absolute percentage error","score":0.5761260986328125},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.498950719833374},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4925316274166107},{"id":"https://openalex.org/keywords/ant-colony-optimization-algorithms","display_name":"Ant colony optimization algorithms","score":0.47204527258872986},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4539875090122223},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4192526936531067},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4113962948322296},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14791274070739746}],"concepts":[{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.7085553407669067},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6574879884719849},{"id":"https://openalex.org/C150217764","wikidata":"https://www.wikidata.org/wiki/Q6803607","display_name":"Mean absolute percentage error","level":3,"score":0.5761260986328125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.498950719833374},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4925316274166107},{"id":"https://openalex.org/C40128228","wikidata":"https://www.wikidata.org/wiki/Q460851","display_name":"Ant colony optimization algorithms","level":2,"score":0.47204527258872986},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4539875090122223},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4192526936531067},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4113962948322296},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14791274070739746}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218001422520309","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001422520309","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8799999952316284,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1970767283","https://openalex.org/W2006868542","https://openalex.org/W2013845817","https://openalex.org/W2061637117","https://openalex.org/W2080114617","https://openalex.org/W2114213946","https://openalex.org/W2132735659","https://openalex.org/W2149624210","https://openalex.org/W2513650310","https://openalex.org/W2550797816","https://openalex.org/W2804201967","https://openalex.org/W2922056388","https://openalex.org/W2999349943","https://openalex.org/W3014068278","https://openalex.org/W3080189037","https://openalex.org/W3081626762","https://openalex.org/W3092339997","https://openalex.org/W3109352822","https://openalex.org/W3130499959","https://openalex.org/W3139484821","https://openalex.org/W3191555983","https://openalex.org/W3192778626","https://openalex.org/W3204586135","https://openalex.org/W3206352320","https://openalex.org/W4205459297","https://openalex.org/W4206006196","https://openalex.org/W4221025993"],"related_works":["https://openalex.org/W4210644201","https://openalex.org/W4285102093","https://openalex.org/W3208495680","https://openalex.org/W2807954395","https://openalex.org/W2787045460","https://openalex.org/W3080840844","https://openalex.org/W4283367183","https://openalex.org/W3121540092","https://openalex.org/W4327774331","https://openalex.org/W2778123278"],"abstract_inverted_index":{"Globally,":[0],"traffic":[1,34,53,95],"accidents":[2,35,54,96],"are":[3,77,147],"of":[4,8,26,52,212],"main":[5],"concern":[6],"because":[7],"more":[9],"death":[10],"rates":[11],"and":[12,41,85,97,114,141,171,206,215],"economic":[13,43,69],"losses":[14,44],"every":[15],"year.":[16],"Thus,":[17],"road":[18,98,133,169],"accident":[19,74,134,170],"severity":[20,135],"is":[21,130,157,177],"the":[22,30,72,87,101,109,150,162,168,180,198],"most":[23],"important":[24],"issue":[25],"concern,":[27],"mainly":[28],"in":[29,37,45],"undeveloped":[31],"countries.":[32],"Generally,":[33],"result":[36],"severe":[38],"human":[39,91],"fatalities":[40],"large":[42],"real-world":[46],"circumstances.":[47],"Moreover,":[48],"appropriate,":[49],"precise":[50],"prediction":[51,75],"has":[55],"a":[56],"high":[57],"probability":[58],"with":[59,80,197],"regard":[60],"to":[61,160],"safeguarding":[62],"public":[63],"security":[64],"as":[65,67],"well":[66],"decreasing":[68],"losses.":[70],"Hence,":[71],"conventional":[73,102],"techniques":[76],"usually":[78],"devised":[79],"statistical":[81],"evaluations,":[82],"which":[83],"identify":[84],"evaluate":[86],"fundamental":[88],"relationships":[89],"among":[90],"variability,":[92],"environmental":[93],"aspects,":[94],"geometry.":[99],"However,":[100],"approaches":[103],"have":[104],"major":[105],"restrictions":[106],"based":[107],"on":[108],"assumptions":[110],"regarding":[111],"function":[112],"kind":[113],"data":[115],"distribution.":[116],"In":[117],"this":[118],"paper,":[119],"Aquila":[120],"Anti-Coronavirus":[121],"Optimization-based":[122],"Deep":[123,128,142,165,175,190],"Long":[124],"Short-Term":[125],"Memory":[126],"(AACO-based":[127],"LSTM)":[129],"developed":[131,188],"for":[132,149,184],"detection.":[136],"Spearman\u2019s":[137],"rank":[138],"correlation":[139],"coefficient":[140],"Recurrent":[143],"Neural":[144],"Network":[145],"(DRNN)":[146],"utilized":[148],"feature":[151],"fusion":[152],"process.":[153],"Data":[154],"augmentation":[155],"method":[156],"carried":[158],"out":[159],"improve":[161],"detection":[163],"performance.":[164,186],"LSTM":[166,176,191],"detects":[167],"its":[172],"severity,":[173],"where":[174],"trained":[178],"by":[179],"designed":[181],"AACO":[182],"algorithm":[183],"better":[185],"The":[187],"AACO-based":[189],"model":[192],"outperformed":[193],"other":[194],"existing":[195],"methods":[196],"Mean":[199,207],"Square":[200],"Error":[201,204,210],"(MSE),":[202],"Root-Mean-Square":[203],"(RMSE)":[205],"Absolute":[208],"Percentage":[209],"(MAPE)":[211],"0.0145,":[213],"0.1204":[214],"0.075%,":[216],"respectively.":[217]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
