{"id":"https://openalex.org/W4376852296","doi":"https://doi.org/10.1145/3573942.3573998","title":"An Improved Particle Filter Passive Location Method Based on Differential Squirrel Search Algorithm","display_name":"An Improved Particle Filter Passive Location Method Based on Differential Squirrel Search Algorithm","publication_year":2022,"publication_date":"2022-09-23","ids":{"openalex":"https://openalex.org/W4376852296","doi":"https://doi.org/10.1145/3573942.3573998"},"language":"en","primary_location":{"id":"doi:10.1145/3573942.3573998","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3573942.3573998","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition","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/A5100681895","display_name":"Jie Yang","orcid":"https://orcid.org/0000-0002-2734-5071"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jie Yang","raw_affiliation_strings":["Xi'an University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0002-2734-5071","affiliations":[{"raw_affiliation_string":"Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039171520","display_name":"Ersen Zhang","orcid":"https://orcid.org/0000-0001-5001-0897"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ersen Zhang","raw_affiliation_strings":["Xi'an University of Posts and Telecommunications, China"],"raw_orcid":"https://orcid.org/0000-0001-5001-0897","affiliations":[{"raw_affiliation_string":"Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100681895"],"corresponding_institution_ids":["https://openalex.org/I4210136859"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18999763,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1098","last_page":"1104"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9976999759674072,"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"}},"topics":[{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9976999759674072,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9907000064849854,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.988099992275238,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/algorithm","display_name":"Algorithm","score":0.6661977767944336},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.6019939184188843},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5916248559951782},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.5370527505874634},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5221845507621765},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.4181874990463257},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3924362063407898},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.37371912598609924},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36199578642845154},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.35974979400634766},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.3305216431617737},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.190145343542099},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.12764284014701843},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.081880122423172}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6661977767944336},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.6019939184188843},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5916248559951782},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.5370527505874634},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5221845507621765},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.4181874990463257},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3924362063407898},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.37371912598609924},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36199578642845154},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.35974979400634766},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.3305216431617737},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.190145343542099},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.12764284014701843},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.081880122423172},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3573942.3573998","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3573942.3573998","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2096902858","https://openalex.org/W2149176438","https://openalex.org/W2950903602","https://openalex.org/W2952915029","https://openalex.org/W2966174082","https://openalex.org/W2969684095","https://openalex.org/W3085783018","https://openalex.org/W3094282801","https://openalex.org/W3127477169","https://openalex.org/W3164219936","https://openalex.org/W3198733406","https://openalex.org/W3199988549"],"related_works":["https://openalex.org/W2015530857","https://openalex.org/W2102148524","https://openalex.org/W2556064263","https://openalex.org/W1991846142","https://openalex.org/W1583020711","https://openalex.org/W1521151968","https://openalex.org/W2128655648","https://openalex.org/W2900672867","https://openalex.org/W1690802106","https://openalex.org/W2033368883"],"abstract_inverted_index":{"Particle":[0],"filtering":[1],"is":[2,27,69,125],"a":[3,58,144],"standard":[4,23,153],"method":[5],"for":[6],"parameter":[7],"estimation":[8],"in":[9,17],"passive":[10,176],"location":[11,52,113,177],"and":[12,19,36,80,156],"has":[13,143],"great":[14],"application":[15],"value":[16],"nonlinear":[18],"non-Gaussian":[20,167],"systems.":[21],"The":[22,71,90,135,169],"particle":[24,33,37],"filter":[25],"(PF)":[26],"prone":[28],"to":[29,84,96,127],"the":[30,40,47,51,85,88,97,100,105,112,129,140,152,157,175,179],"problem":[31],"of":[32,42,50,87,99,108,115,161,178],"weight":[34,86],"degradation":[35],"dilution":[38],"as":[39],"number":[41],"iterations":[43],"increases,":[44],"which":[45],"affects":[46],"overall":[48],"performance":[49],"algorithm.":[53],"Aiming":[54],"at":[55],"this":[56],"problem,":[57],"PF":[59,154,159],"algorithm":[60,66,130,142,155,171],"based":[61],"on":[62],"differential":[63],"squirrel":[64],"search":[65],"(DSSA)":[67],"optimization":[68,164],"proposed.":[70],"particles":[72,92,102,117],"are":[73,93],"divided":[74],"into":[75,132],"optimal":[76],"individuals,":[77,79],"sub-optimal":[78],"ordinary":[81],"individuals":[82],"according":[83],"particles.":[89],"low-weight":[91],"moved":[94],"closer":[95],"position":[98],"high-weight":[101],"by":[103],"simulating":[104],"predation":[106],"behavior":[107],"squirrels,":[109],"so":[110],"that":[111,139],"information":[114],"most":[116],"can":[118,172],"be":[119],"retained.":[120],"And":[121],"seasonal":[122],"monitoring":[123],"condition":[124],"used":[126],"avoid":[128],"falling":[131],"local":[133],"optimal.":[134],"simulation":[136],"results":[137],"show":[138],"improved":[141,158,170],"lower":[145],"root":[146],"mean":[147],"square":[148],"error":[149],"(RMSE)":[150],"than":[151],"algorithms":[160,165],"other":[162],"intelligent":[163],"under":[166],"noise.":[168],"accurately":[173],"achieve":[174],"moving":[180],"target.":[181]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
