{"id":"https://openalex.org/W2477564998","doi":"https://doi.org/10.1109/acc.2016.7526155","title":"Deep causal mining for plant-wide oscillations with multilevel Granger causality analysis","display_name":"Deep causal mining for plant-wide oscillations with multilevel Granger causality analysis","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2477564998","doi":"https://doi.org/10.1109/acc.2016.7526155","mag":"2477564998"},"language":"en","primary_location":{"id":"doi:10.1109/acc.2016.7526155","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acc.2016.7526155","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":null,"display_name":"Tao Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tao Yuan","raw_affiliation_strings":["Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100438619","display_name":"Gang Li","orcid":"https://orcid.org/0000-0001-6102-969X"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gang Li","raw_affiliation_strings":["Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044542322","display_name":"Zhaohui Zhang","orcid":"https://orcid.org/0009-0001-7737-7274"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhaohui Zhang","raw_affiliation_strings":["Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056937548","display_name":"S. Joe Qin","orcid":"https://orcid.org/0000-0001-7631-2535"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"S. Joe Qin","raw_affiliation_strings":["Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA","institution_ids":["https://openalex.org/I1174212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1174212"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5056","last_page":"5061"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9995999932289124,"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":0.9995999932289124,"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/T10791","display_name":"Advanced Control Systems Optimization","score":0.9811000227928162,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9587000012397766,"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/granger-causality","display_name":"Granger causality","score":0.9097551107406616},{"id":"https://openalex.org/keywords/multicollinearity","display_name":"Multicollinearity","score":0.6580029726028442},{"id":"https://openalex.org/keywords/causality","display_name":"Causality (physics)","score":0.6419437527656555},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.591147780418396},{"id":"https://openalex.org/keywords/root-cause","display_name":"Root cause","score":0.5571889281272888},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5047899484634399},{"id":"https://openalex.org/keywords/causal-model","display_name":"Causal model","score":0.4566851854324341},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.45413124561309814},{"id":"https://openalex.org/keywords/dynamic-time-warping","display_name":"Dynamic time warping","score":0.438308984041214},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3809431195259094},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35341185331344604},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32673972845077515},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2894589900970459},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2812594771385193},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16216173768043518},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.13294872641563416}],"concepts":[{"id":"https://openalex.org/C129824826","wikidata":"https://www.wikidata.org/wiki/Q2630107","display_name":"Granger causality","level":2,"score":0.9097551107406616},{"id":"https://openalex.org/C189285262","wikidata":"https://www.wikidata.org/wiki/Q1332350","display_name":"Multicollinearity","level":3,"score":0.6580029726028442},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.6419437527656555},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.591147780418396},{"id":"https://openalex.org/C84945661","wikidata":"https://www.wikidata.org/wiki/Q7366567","display_name":"Root cause","level":2,"score":0.5571889281272888},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5047899484634399},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.4566851854324341},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45413124561309814},{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.438308984041214},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3809431195259094},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35341185331344604},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32673972845077515},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2894589900970459},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2812594771385193},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16216173768043518},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.13294872641563416},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acc.2016.7526155","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acc.2016.7526155","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":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W116902681","https://openalex.org/W1984226456","https://openalex.org/W1984380467","https://openalex.org/W1990058302","https://openalex.org/W1995969522","https://openalex.org/W2010626297","https://openalex.org/W2016603617","https://openalex.org/W2023685972","https://openalex.org/W2036630575","https://openalex.org/W2061824367","https://openalex.org/W2097543469","https://openalex.org/W2129918244","https://openalex.org/W2137464508","https://openalex.org/W4234722734","https://openalex.org/W6604828220"],"related_works":["https://openalex.org/W2229495757","https://openalex.org/W210577557","https://openalex.org/W2935056047","https://openalex.org/W2094981715","https://openalex.org/W4293757468","https://openalex.org/W2888841658","https://openalex.org/W2188829624","https://openalex.org/W2093292986","https://openalex.org/W2971843680","https://openalex.org/W3173290906"],"abstract_inverted_index":{"Plant-wide":[0],"disturbance":[1],"such":[2],"as":[3,64],"oscillations":[4],"are":[5],"common":[6],"in":[7],"large-scale":[8],"complex":[9],"controlled":[10],"processes":[11],"whose":[12],"effects":[13],"propagate":[14],"to":[15,27,104,121],"many":[16],"units":[17],"and":[18,36,77,125],"may":[19],"deteriorate":[20],"overall":[21],"control":[22],"performance.":[23],"It":[24],"is":[25,62,69,86,102,113],"important":[26],"capture":[28],"the":[29,34,38],"major":[30],"causal":[31,88,100],"relationship":[32],"within":[33,90],"plant":[35],"diagnose":[37],"root":[39,56],"cause":[40,57],"along":[41],"with":[42],"complete":[43],"propagation":[44],"paths.":[45],"This":[46],"paper":[47],"presents":[48],"a":[49,65,94,116],"novel":[50],"multilevel":[51],"Granger":[52,81,99],"causality":[53,110],"framework":[54,112],"for":[55],"diagnosis.":[58],"The":[59,83,108],"high":[60],"level":[61,85],"regarded":[63],"group-wise":[66],"analysis,":[67],"which":[68],"clustered":[70],"by":[71],"dynamic":[72],"time":[73],"warping-based":[74],"K-means":[75],"method":[76],"investigated":[78],"using":[79],"group":[80,92],"causality.":[82],"low":[84],"individual":[87],"reasoning":[89],"each":[91],"where":[93],"partial":[95],"least":[96],"squares":[97],"modified":[98],"test":[101],"developed":[103],"overcome":[105],"multicollinearity":[106],"issue.":[107],"proposed":[109],"analysis":[111],"validated":[114],"through":[115],"benchmark":[117],"industrial":[118],"case":[119],"study":[120],"show":[122],"its":[123],"effectiveness":[124],"superiority.":[126]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
