{"id":"https://openalex.org/W2344954093","doi":"https://doi.org/10.1109/tsmc.2015.2503382","title":"Spatial Sensor Selection via Gaussian Markov Random Fields","display_name":"Spatial Sensor Selection via Gaussian Markov Random Fields","publication_year":2015,"publication_date":"2015-12-24","ids":{"openalex":"https://openalex.org/W2344954093","doi":"https://doi.org/10.1109/tsmc.2015.2503382","mag":"2344954093"},"language":"en","primary_location":{"id":"doi:10.1109/tsmc.2015.2503382","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2015.2503382","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Systems, Man, and Cybernetics: Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://opus.lib.uts.edu.au/bitstream/10453/88527/4/2-s2.0-84983535163%20am%20%281%29.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051920398","display_name":"Linh Nguyen","orcid":"https://orcid.org/0000-0001-5360-886X"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Linh V. Nguyen","raw_affiliation_strings":["Centre for Autonomous Systems, University of Technology, Sydney, NSW, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centre for Autonomous Systems, University of Technology, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053565868","display_name":"Sarath Kodagoda","orcid":"https://orcid.org/0000-0001-5175-9138"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Sarath Kodagoda","raw_affiliation_strings":["Centre for Autonomous Systems, University of Technology, Sydney, NSW, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centre for Autonomous Systems, University of Technology, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088672153","display_name":"Ravindra Ranasinghe","orcid":"https://orcid.org/0000-0002-3785-3723"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Ravindra Ranasinghe","raw_affiliation_strings":["Centre for Autonomous Systems, University of Technology, Sydney, NSW, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centre for Autonomous Systems, University of Technology, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I114017466"],"apc_list":null,"apc_paid":null,"fwci":1.4117,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":{"value":0.83946259,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"46","issue":"9","first_page":"1226","last_page":"1239"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9779000282287598,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9732999801635742,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6331068277359009},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6036633253097534},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5999894738197327},{"id":"https://openalex.org/keywords/random-field","display_name":"Random field","score":0.5481354594230652},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.5336436033248901},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4662299156188965},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39339619874954224},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3789352476596832},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31129908561706543},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.24664393067359924},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.20478355884552002},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.204219251871109}],"concepts":[{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6331068277359009},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6036633253097534},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5999894738197327},{"id":"https://openalex.org/C130402806","wikidata":"https://www.wikidata.org/wiki/Q5361768","display_name":"Random field","level":2,"score":0.5481354594230652},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.5336436033248901},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4662299156188965},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39339619874954224},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3789352476596832},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31129908561706543},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.24664393067359924},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.20478355884552002},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.204219251871109},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tsmc.2015.2503382","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2015.2503382","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Systems, Man, and Cybernetics: Systems","raw_type":"journal-article"},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/88527","is_oa":true,"landing_page_url":"http://hdl.handle.net/10453/88527","pdf_url":"https://opus.lib.uts.edu.au/bitstream/10453/88527/4/2-s2.0-84983535163%20am%20%281%29.pdf","source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"}],"best_oa_location":{"id":"pmh:oai:opus.lib.uts.edu.au:10453/88527","is_oa":true,"landing_page_url":"http://hdl.handle.net/10453/88527","pdf_url":"https://opus.lib.uts.edu.au/bitstream/10453/88527/4/2-s2.0-84983535163%20am%20%281%29.pdf","source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320967","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2344954093.pdf","grobid_xml":"https://content.openalex.org/works/W2344954093.grobid-xml"},"referenced_works_count":60,"referenced_works":["https://openalex.org/W129305155","https://openalex.org/W143236119","https://openalex.org/W161199568","https://openalex.org/W391578156","https://openalex.org/W1663973292","https://openalex.org/W1680189815","https://openalex.org/W1746819321","https://openalex.org/W1788292158","https://openalex.org/W1837874438","https://openalex.org/W1967011851","https://openalex.org/W1995378794","https://openalex.org/W1999824796","https://openalex.org/W2004207982","https://openalex.org/W2008246569","https://openalex.org/W2008291228","https://openalex.org/W2008567526","https://openalex.org/W2011189221","https://openalex.org/W2014018052","https://openalex.org/W2024060531","https://openalex.org/W2025333932","https://openalex.org/W2030597423","https://openalex.org/W2042545035","https://openalex.org/W2048811510","https://openalex.org/W2060496070","https://openalex.org/W2069876697","https://openalex.org/W2070005700","https://openalex.org/W2077053528","https://openalex.org/W2098642746","https://openalex.org/W2105837036","https://openalex.org/W2107969104","https://openalex.org/W2114771311","https://openalex.org/W2125481309","https://openalex.org/W2130761473","https://openalex.org/W2131824593","https://openalex.org/W2141993787","https://openalex.org/W2143022286","https://openalex.org/W2144898279","https://openalex.org/W2144931885","https://openalex.org/W2156195892","https://openalex.org/W2156675727","https://openalex.org/W2157104853","https://openalex.org/W2168452204","https://openalex.org/W2169607271","https://openalex.org/W2208102648","https://openalex.org/W2296319761","https://openalex.org/W2314082161","https://openalex.org/W2478708596","https://openalex.org/W2594639291","https://openalex.org/W2610857016","https://openalex.org/W2796739798","https://openalex.org/W2947553656","https://openalex.org/W3003506411","https://openalex.org/W3145289772","https://openalex.org/W4211049957","https://openalex.org/W4245192389","https://openalex.org/W4250589301","https://openalex.org/W4293244076","https://openalex.org/W4300031234","https://openalex.org/W4301341693","https://openalex.org/W6679608865"],"related_works":["https://openalex.org/W1660242800","https://openalex.org/W2077211377","https://openalex.org/W4205762803","https://openalex.org/W1006270037","https://openalex.org/W3152686072","https://openalex.org/W1489542724","https://openalex.org/W2554371957","https://openalex.org/W82723519","https://openalex.org/W4297779544","https://openalex.org/W2757253340"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"the":[3,7,42,46,122,127,142,148],"problem":[4],"of":[5,13,41,116,121,141,147],"selecting":[6],"most":[8],"informative":[9],"sensor":[10,26,55,80,104],"locations":[11,70,75],"out":[12],"all":[14],"possible":[15],"sensing":[16],"positions":[17],"in":[18,101,126],"predicting":[19],"spatial":[20,29,54],"phenomena":[21],"by":[22,33,106,137],"using":[23,155],"a":[24,102,107],"wireless":[25],"network.":[27],"The":[28,87,145],"field":[30],"is":[31,58,91,134,151],"modeled":[32],"Gaussian":[34],"Markov":[35],"random":[36,66],"fields":[37],"(GMRFs),":[38],"where":[39],"sparsity":[40],"precision":[43],"matrix":[44],"enables":[45],"network":[47],"to":[48,94],"benefit":[49],"from":[50],"computation.":[51],"A":[52],"new":[53],"selection":[56,129],"criterion":[57,90],"proposed":[59,128,149],"based":[60],"on":[61],"mutual":[62],"information":[63],"(MI)":[64],"between":[65],"variables":[67],"at":[68,73,138],"selected":[69],"and":[71,76,97,118,153],"those":[72],"unselected":[74],"interested":[77],"but":[78],"unlikely":[79],"placed":[81],"positions,":[82],"which":[83],"enhances":[84],"resulting":[85],"prediction.":[86],"GMRF-based":[88],"optimality":[89],"then":[92],"proven":[93],"be":[95],"computationally":[96],"efficiently":[98],"resolved,":[99],"especially":[100],"large-scale":[103],"network,":[105],"polynomial":[108],"time":[109],"approximation":[110],"algorithm.":[111],"More":[112],"importantly,":[113],"with":[114,161],"demonstrations":[115],"monotonicity":[117],"submodularity":[119],"properties":[120],"MI":[123],"set":[124],"function":[125],"criterion,":[130],"our":[131],"near-optimal":[132],"solution":[133],"also":[135],"guaranteed":[136],"least":[139],"within(1-1/e)":[140],"optimal":[143],"performance.":[144],"effectiveness":[146],"approach":[150],"compared":[152],"illustrated":[154],"two":[156],"real-life":[157],"large":[158],"data":[159],"sets":[160],"promising":[162],"results.":[163]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}