{"id":"https://openalex.org/W2503979353","doi":"https://doi.org/10.1109/acc.2016.7526152","title":"Algorithmic modelling of structural connectivity for process plants","display_name":"Algorithmic modelling of structural connectivity for process plants","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2503979353","doi":"https://doi.org/10.1109/acc.2016.7526152","mag":"2503979353"},"language":"en","primary_location":{"id":"doi:10.1109/acc.2016.7526152","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acc.2016.7526152","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 American Control Conference (ACC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5021156347","display_name":"Temitayo Bankole","orcid":"https://orcid.org/0000-0002-5840-9824"},"institutions":[{"id":"https://openalex.org/I12097938","display_name":"West Virginia University","ror":"https://ror.org/011vxgd24","country_code":"US","type":"education","lineage":["https://openalex.org/I12097938"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Temitayo Bankole","raw_affiliation_strings":["Department of Chemical Engineering, West Virginia University, Morgantown, WV, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Chemical Engineering, West Virginia University, Morgantown, WV, USA","institution_ids":["https://openalex.org/I12097938"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037148093","display_name":"Debangsu Bhattacharyya","orcid":"https://orcid.org/0000-0001-9957-7528"},"institutions":[{"id":"https://openalex.org/I12097938","display_name":"West Virginia University","ror":"https://ror.org/011vxgd24","country_code":"US","type":"education","lineage":["https://openalex.org/I12097938"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Debangsu Bhattacharyya","raw_affiliation_strings":["Department of Chemical Engineering, West Virginia University, Morgantown, WV, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Chemical Engineering, West Virginia University, Morgantown, WV, USA","institution_ids":["https://openalex.org/I12097938"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I12097938"],"apc_list":null,"apc_paid":null,"fwci":1.7615,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.81512521,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"63","issue":null,"first_page":"5038","last_page":"5043"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/T11434","display_name":"Electrochemical Analysis and Applications","score":0.9861000180244446,"subfield":{"id":"https://openalex.org/subfields/1603","display_name":"Electrochemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9846000075340271,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6750892996788025},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.5407746434211731},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5270479321479797},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.4746188223361969},{"id":"https://openalex.org/keywords/process-control","display_name":"Process control","score":0.420280784368515},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39201176166534424},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3548988699913025},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33541613817214966},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17073863744735718}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6750892996788025},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.5407746434211731},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5270479321479797},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.4746188223361969},{"id":"https://openalex.org/C155386361","wikidata":"https://www.wikidata.org/wiki/Q1649571","display_name":"Process control","level":3,"score":0.420280784368515},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39201176166534424},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3548988699913025},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33541613817214966},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17073863744735718},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acc.2016.7526152","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acc.2016.7526152","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 American Control Conference (ACC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.550000011920929,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1972446782","https://openalex.org/W1978510898","https://openalex.org/W2057393527","https://openalex.org/W2068341210","https://openalex.org/W2073092393","https://openalex.org/W2079780979","https://openalex.org/W2109363714","https://openalex.org/W2117663940","https://openalex.org/W2130382978","https://openalex.org/W2131353535","https://openalex.org/W2131588967","https://openalex.org/W2149153247","https://openalex.org/W2169005503","https://openalex.org/W2308025244","https://openalex.org/W2509438098","https://openalex.org/W4285719527","https://openalex.org/W6679301673","https://openalex.org/W6679774218","https://openalex.org/W6698126503","https://openalex.org/W6725288581"],"related_works":["https://openalex.org/W2947806671","https://openalex.org/W2972991241","https://openalex.org/W2390878257","https://openalex.org/W2961085424","https://openalex.org/W4286629047","https://openalex.org/W2144260821","https://openalex.org/W2381390841","https://openalex.org/W4224009465","https://openalex.org/W2037938733","https://openalex.org/W2001839669"],"abstract_inverted_index":{"In":[0],"this":[1,107],"paper,":[2],"we":[3],"propose":[4],"a":[5,21,32,54,68,77,112],"new":[6],"systematic":[7],"methodology":[8],"to":[9,26,34,39,59,85],"identify":[10],"dynamic":[11,36,118],"changes":[12],"in":[13,20,111],"the":[14,29,41,61,64],"connectivity":[15,45,65],"among":[16,46],"various":[17],"equipment":[18,47,98],"items":[19,99],"process":[22,88,124],"plant.":[23],"Drawing":[24],"analogy":[25],"neurological":[27],"systems,":[28],"paper":[30],"develops":[31],"framework":[33,56],"obtain":[35,60],"causal":[37],"model":[38],"capture":[40],"intrinsic":[42],"and":[43,92],"stimulus-driven":[44],"items.":[48],"An":[49],"expectation":[50],"maximization":[51],"algorithm":[52,73],"following":[53],"Bayesian":[55],"is":[57,74],"employed":[58],"elements":[62],"of":[63,122],"matrices":[66],"using":[67],"maximum":[69],"likelihood":[70],"approach.":[71],"The":[72,80],"tested":[75],"on":[76],"reactor-separator":[78],"system.":[79],"proposed":[81],"approach":[82,108],"can":[83,109],"help":[84],"decompose":[86],"large-scale":[87,123],"plants":[89],"into":[90],"strongly-connected":[91,97],"weakly-connected":[93],"systems.":[94],"If":[95],"only":[96],"are":[100],"considered":[101],"together":[102],"for":[103,117],"control":[104],"structure":[105],"selection,":[106],"result":[110],"computationally":[113],"less":[114],"intensive":[115],"problem":[116],"controlled":[119],"variable":[120],"selection":[121],"plants.":[125]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
