{"id":"https://openalex.org/W3095794531","doi":"https://doi.org/10.1109/mfi49285.2020.9235241","title":"Mathematical Modeling and Optimal Inference of Guided Markov-Like Trajectory","display_name":"Mathematical Modeling and Optimal Inference of Guided Markov-Like Trajectory","publication_year":2020,"publication_date":"2020-09-14","ids":{"openalex":"https://openalex.org/W3095794531","doi":"https://doi.org/10.1109/mfi49285.2020.9235241","mag":"3095794531"},"language":"en","primary_location":{"id":"doi:10.1109/mfi49285.2020.9235241","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mfi49285.2020.9235241","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)","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/A5031408792","display_name":"Reza Rezaie","orcid":"https://orcid.org/0000-0002-1204-4794"},"institutions":[{"id":"https://openalex.org/I192396691","display_name":"University of New Orleans","ror":"https://ror.org/034mtvk83","country_code":"US","type":"education","lineage":["https://openalex.org/I192396691","https://openalex.org/I2799628689"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Reza Rezaie","raw_affiliation_strings":["Department of Electrical Engineering, University of New Orleans, New Orleans, LA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of New Orleans, New Orleans, LA","institution_ids":["https://openalex.org/I192396691"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008364423","display_name":"X. Rong Li","orcid":null},"institutions":[{"id":"https://openalex.org/I192396691","display_name":"University of New Orleans","ror":"https://ror.org/034mtvk83","country_code":"US","type":"education","lineage":["https://openalex.org/I192396691","https://openalex.org/I2799628689"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"X. Rong Li","raw_affiliation_strings":["Department of Electrical Engineering, University of New Orleans, New Orleans, LA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of New Orleans, New Orleans, LA","institution_ids":["https://openalex.org/I192396691"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5031408792"],"corresponding_institution_ids":["https://openalex.org/I192396691"],"apc_list":null,"apc_paid":null,"fwci":0.1954,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.50688983,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"26","last_page":"31"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9980999827384949,"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/T10249","display_name":"Distributed Control Multi-Agent Systems","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.8502499461174011},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6221253275871277},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.6208993196487427},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5752772092819214},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5746705532073975},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.46976304054260254},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.4669547975063324},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3879448175430298},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3833015263080597},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25256478786468506},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.15088710188865662},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10503530502319336},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07394176721572876}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.8502499461174011},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6221253275871277},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.6208993196487427},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5752772092819214},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5746705532073975},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.46976304054260254},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4669547975063324},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3879448175430298},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3833015263080597},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25256478786468506},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.15088710188865662},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10503530502319336},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07394176721572876},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mfi49285.2020.9235241","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mfi49285.2020.9235241","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)","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":31,"referenced_works":["https://openalex.org/W40650588","https://openalex.org/W1966994025","https://openalex.org/W1968476015","https://openalex.org/W1970035417","https://openalex.org/W1979785016","https://openalex.org/W1994195074","https://openalex.org/W2006866209","https://openalex.org/W2026387372","https://openalex.org/W2035874719","https://openalex.org/W2128426080","https://openalex.org/W2140242774","https://openalex.org/W2146243646","https://openalex.org/W2146705677","https://openalex.org/W2160484294","https://openalex.org/W2160664904","https://openalex.org/W2160920523","https://openalex.org/W2161140693","https://openalex.org/W2168938915","https://openalex.org/W2219299986","https://openalex.org/W2312311608","https://openalex.org/W2321767198","https://openalex.org/W2331083093","https://openalex.org/W2594388303","https://openalex.org/W2775541648","https://openalex.org/W2899765703","https://openalex.org/W2901325619","https://openalex.org/W2904211149","https://openalex.org/W2963414935","https://openalex.org/W2966925178","https://openalex.org/W2995384287","https://openalex.org/W6700701042"],"related_works":["https://openalex.org/W2379651310","https://openalex.org/W2113019827","https://openalex.org/W1541249122","https://openalex.org/W2084326697","https://openalex.org/W2027903142","https://openalex.org/W2354322608","https://openalex.org/W2804608325","https://openalex.org/W2077211377","https://openalex.org/W2413828414","https://openalex.org/W2186675474"],"abstract_inverted_index":{"A":[0,44,73],"trajectory":[1,34,42,98,107,151],"of":[2,46,65,84,89,99],"a":[3,15,24,33,62,69,85,90,94,100,105,111,120,123,126,134],"destination-directed":[4,41],"moving":[5,95,127],"object":[6,92,102],"(e.g.":[7],"an":[8,11,22],"aircraft":[9],"from":[10],"origin":[12],"airport":[13],"to":[14,133],"destination":[16,40],"airport)":[17],"has":[18,57],"three":[19],"main":[20,60],"components:":[21,61],"origin,":[23],"destination,":[25],"and":[26,68,150],"motion":[27],"in":[28],"between.":[29],"We":[30,146],"call":[31],"such":[32],"that":[35],"end":[36],"up":[37],"at":[38],"the":[39,58,82,141,155],"(DDT).":[43],"class":[45],"conditionally":[47],"Markov":[48],"(CM)":[49],"sequences":[50],"(called":[51],"CM":[52,74,112,135],"<inf":[53,75,113,136],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[54,76,114,137],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">L</inf>":[55,77,115,138],")":[56],"following":[59],"joint":[63],"density":[64],"two":[66],"endpoints":[67],"Markov-like":[70],"evolution":[71,83],"law.":[72],"dynamic":[78],"model":[79,121,131,139],"can":[80],"describe":[81],"DDT":[86],"but":[87],"not":[88,144],"guided":[91,101,106],"chasing":[93],"guide.":[96,128],"The":[97,129],"is":[103,143],"called":[104],"(GT).":[108],"Inspired":[109],"by":[110],"model,":[116],"this":[117],"paper":[118],"proposes":[119],"for":[122],"GT":[124],"with":[125],"proposed":[130,156],"reduces":[132],"if":[140],"guide":[142],"moving.":[145],"also":[147],"study":[148],"filtering":[149],"prediction":[152],"based":[153],"on":[154],"model.":[157],"Simulation":[158],"results":[159],"are":[160],"presented.":[161]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
