{"id":"https://openalex.org/W2121142533","doi":"https://doi.org/10.1007/s10588-010-9066-2","title":"A Bayesian approach to modeling lost person behaviors based on terrain features in Wilderness Search and\u00a0Rescue","display_name":"A Bayesian approach to modeling lost person behaviors based on terrain features in Wilderness Search and\u00a0Rescue","publication_year":2010,"publication_date":"2010-07-29","ids":{"openalex":"https://openalex.org/W2121142533","doi":"https://doi.org/10.1007/s10588-010-9066-2","mag":"2121142533"},"language":"en","primary_location":{"id":"doi:10.1007/s10588-010-9066-2","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s10588-010-9066-2","pdf_url":null,"source":{"id":"https://openalex.org/S47778307","display_name":"Computational and Mathematical Organization Theory","issn_l":"1381-298X","issn":["1381-298X","1572-9346"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational and Mathematical Organization Theory","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/A5062040468","display_name":"Lanny Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Lanny Lin","raw_affiliation_strings":["Computer Science Department, Brigham Young University, 3361 TMCB, Provo, UT 84602, USA","Computer Science Department, Brigham Young University, Provo, USA UT 84602#TAB#"],"affiliations":[{"raw_affiliation_string":"Computer Science Department, Brigham Young University, 3361 TMCB, Provo, UT 84602, USA","institution_ids":["https://openalex.org/I100005738"]},{"raw_affiliation_string":"Computer Science Department, Brigham Young University, Provo, USA UT 84602#TAB#","institution_ids":["https://openalex.org/I100005738"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077345598","display_name":"Michael A. Goodrich","orcid":"https://orcid.org/0000-0002-2489-5705"},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael A. Goodrich","raw_affiliation_strings":["Computer Science Department, Brigham Young University, 3361 TMCB, Provo, UT 84602, USA","Computer Science Department, Brigham Young University, Provo, USA UT 84602#TAB#"],"affiliations":[{"raw_affiliation_string":"Computer Science Department, Brigham Young University, 3361 TMCB, Provo, UT 84602, USA","institution_ids":["https://openalex.org/I100005738"]},{"raw_affiliation_string":"Computer Science Department, Brigham Young University, Provo, USA UT 84602#TAB#","institution_ids":["https://openalex.org/I100005738"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5062040468"],"corresponding_institution_ids":["https://openalex.org/I100005738"],"apc_list":{"value":2090,"currency":"EUR","value_usd":2690},"apc_paid":null,"fwci":4.6954,"has_fulltext":false,"cited_by_count":83,"citation_normalized_percentile":{"value":0.94859179,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"16","issue":"3","first_page":"300","last_page":"323"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.989300012588501,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.989300012588501,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9886000156402588,"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/T12288","display_name":"Optimization and Search Problems","score":0.9700000286102295,"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/computer-science","display_name":"Computer science","score":0.6946450471878052},{"id":"https://openalex.org/keywords/terrain","display_name":"Terrain","score":0.6792397499084473},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.6058785319328308},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5933794379234314},{"id":"https://openalex.org/keywords/wilderness","display_name":"Wilderness","score":0.5326098203659058},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5189599394798279},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5079548954963684},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.5031895041465759},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.42059633135795593},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33718371391296387},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1814734935760498},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.11525458097457886}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6946450471878052},{"id":"https://openalex.org/C161840515","wikidata":"https://www.wikidata.org/wiki/Q186131","display_name":"Terrain","level":2,"score":0.6792397499084473},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.6058785319328308},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5933794379234314},{"id":"https://openalex.org/C2778677346","wikidata":"https://www.wikidata.org/wiki/Q911871","display_name":"Wilderness","level":2,"score":0.5326098203659058},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5189599394798279},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5079548954963684},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5031895041465759},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.42059633135795593},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33718371391296387},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1814734935760498},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.11525458097457886},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s10588-010-9066-2","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s10588-010-9066-2","pdf_url":null,"source":{"id":"https://openalex.org/S47778307","display_name":"Computational and Mathematical Organization Theory","issn_l":"1381-298X","issn":["1381-298X","1572-9346"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational and Mathematical Organization Theory","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:spr:comaot:v:16:y:2010:i:3:d:10.1007_s10588-010-9066-2","is_oa":false,"landing_page_url":"http://link.springer.com/10.1007/s10588-010-9066-2","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.47999998927116394}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320338295","display_name":"Army Research Laboratory","ror":"https://ror.org/011hc8f90"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W101015759","https://openalex.org/W1532325173","https://openalex.org/W2045656233","https://openalex.org/W2057765075","https://openalex.org/W2099114258","https://openalex.org/W2099985613","https://openalex.org/W2105889829","https://openalex.org/W2107664584","https://openalex.org/W2115213191","https://openalex.org/W2138138984","https://openalex.org/W2140646056","https://openalex.org/W2142635246","https://openalex.org/W2143707047","https://openalex.org/W2168175751","https://openalex.org/W2950314238","https://openalex.org/W2971826558","https://openalex.org/W2990138404","https://openalex.org/W3049587539","https://openalex.org/W3141742845","https://openalex.org/W3149745985","https://openalex.org/W3202620800","https://openalex.org/W4232383088"],"related_works":["https://openalex.org/W4323796314","https://openalex.org/W3160546271","https://openalex.org/W2147201983","https://openalex.org/W3165312030","https://openalex.org/W3124172274","https://openalex.org/W2106750393","https://openalex.org/W4321613659","https://openalex.org/W2184215046","https://openalex.org/W2095960595","https://openalex.org/W126842942"],"abstract_inverted_index":null,"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":7},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":4}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}