{"id":"https://openalex.org/W2036718387","doi":"https://doi.org/10.1109/bigdata.2014.7004331","title":"An intelligent machine monitoring system for energy prediction using a Gaussian Process regression","display_name":"An intelligent machine monitoring system for energy prediction using a Gaussian Process regression","publication_year":2014,"publication_date":"2014-10-01","ids":{"openalex":"https://openalex.org/W2036718387","doi":"https://doi.org/10.1109/bigdata.2014.7004331","mag":"2036718387"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2014.7004331","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2014.7004331","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Big Data (Big Data)","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/A5051832961","display_name":"Raunak Bhinge","orcid":null},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Raunak Bhinge","raw_affiliation_strings":["Mechanical Engineering, University of California, Berkeley, Berkeley, CA, USA","Mechanical Engineering, University of California Berkeley , Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"Mechanical Engineering, University of California, Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]},{"raw_affiliation_string":"Mechanical Engineering, University of California Berkeley , Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002115631","display_name":"Nishant Biswas","orcid":null},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nishant Biswas","raw_affiliation_strings":["Mechanical Engineering, University of California, Berkeley, Berkeley, CA, USA","Mechanical Engineering, University of California Berkeley , Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"Mechanical Engineering, University of California, Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]},{"raw_affiliation_string":"Mechanical Engineering, University of California Berkeley , Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002687722","display_name":"David Dornfeld","orcid":"https://orcid.org/0000-0002-5177-3295"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Dornfeld","raw_affiliation_strings":["Mechanical Engineering, University of California, Berkeley, Berkeley, CA, USA","Mechanical Engineering, University of California Berkeley , Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"Mechanical Engineering, University of California, Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]},{"raw_affiliation_string":"Mechanical Engineering, University of California Berkeley , Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023509025","display_name":"Jinkyoo Park","orcid":"https://orcid.org/0000-0003-2620-1479"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jinkyoo Park","raw_affiliation_strings":["Civil and Environmental Engineering, Stanford University, Stanford, CA, USA","Civil and Environmental Engineering, Stanford University, Stanford, CA, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Civil and Environmental Engineering, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Civil and Environmental Engineering, Stanford University, Stanford, CA, USA#TAB#","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008053913","display_name":"Kincho H. Law","orcid":"https://orcid.org/0000-0002-9376-7643"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kincho H. Law","raw_affiliation_strings":["Civil and Environmental Engineering, Stanford University, Stanford, CA, USA","Civil and Environmental Engineering, Stanford University, Stanford, CA, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Civil and Environmental Engineering, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Civil and Environmental Engineering, Stanford University, Stanford, CA, USA#TAB#","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065463543","display_name":"Moneer Helu","orcid":"https://orcid.org/0000-0003-3089-4466"},"institutions":[{"id":"https://openalex.org/I1321296531","display_name":"National Institute of Standards and Technology","ror":"https://ror.org/05xpvk416","country_code":"US","type":"funder","lineage":["https://openalex.org/I1321296531","https://openalex.org/I1343035065"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Moneer Helu","raw_affiliation_strings":["Systems Integration Division, National Institute of Standards and Technology, Gaithersburg, MD, USA","Systems Integration Division, National Institute of Standards and Technology, Gaithersburg, MD, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Systems Integration Division, National Institute of Standards and Technology, Gaithersburg, MD, USA","institution_ids":["https://openalex.org/I1321296531"]},{"raw_affiliation_string":"Systems Integration Division, National Institute of Standards and Technology, Gaithersburg, MD, USA#TAB#","institution_ids":["https://openalex.org/I1321296531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060590453","display_name":"Sudarsan Rachuri","orcid":"https://orcid.org/0000-0003-3851-6451"},"institutions":[{"id":"https://openalex.org/I1321296531","display_name":"National Institute of Standards and Technology","ror":"https://ror.org/05xpvk416","country_code":"US","type":"funder","lineage":["https://openalex.org/I1321296531","https://openalex.org/I1343035065"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sudarsan Rachuri","raw_affiliation_strings":["Systems Integration Division, National Institute of Standards and Technology, Gaithersburg, MD, USA","Systems Integration Division, National Institute of Standards and Technology, Gaithersburg, MD, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Systems Integration Division, National Institute of Standards and Technology, Gaithersburg, MD, USA","institution_ids":["https://openalex.org/I1321296531"]},{"raw_affiliation_string":"Systems Integration Division, National Institute of Standards and Technology, Gaithersburg, MD, USA#TAB#","institution_ids":["https://openalex.org/I1321296531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5051832961"],"corresponding_institution_ids":["https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":6.7656,"has_fulltext":false,"cited_by_count":49,"citation_normalized_percentile":{"value":0.96746703,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"978","last_page":"986"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9990000128746033,"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":0.9990000128746033,"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9793999791145325,"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/T10121","display_name":"Building Energy and Comfort Optimization","score":0.9664999842643738,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7006168365478516},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.6849859356880188},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.5829689502716064},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5428202152252197},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.5067229866981506},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5005898475646973},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46499741077423096},{"id":"https://openalex.org/keywords/automation","display_name":"Automation","score":0.46183300018310547},{"id":"https://openalex.org/keywords/predictive-analytics","display_name":"Predictive analytics","score":0.44152015447616577},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.43443530797958374},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43389222025871277},{"id":"https://openalex.org/keywords/energy-management","display_name":"Energy management","score":0.42387181520462036},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1831817328929901},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.0748632550239563},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0689532458782196}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7006168365478516},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.6849859356880188},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.5829689502716064},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5428202152252197},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.5067229866981506},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5005898475646973},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46499741077423096},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.46183300018310547},{"id":"https://openalex.org/C83209312","wikidata":"https://www.wikidata.org/wiki/Q1053367","display_name":"Predictive analytics","level":2,"score":0.44152015447616577},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.43443530797958374},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43389222025871277},{"id":"https://openalex.org/C7817414","wikidata":"https://www.wikidata.org/wiki/Q1779504","display_name":"Energy management","level":3,"score":0.42387181520462036},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1831817328929901},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0748632550239563},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0689532458782196},{"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/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bigdata.2014.7004331","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2014.7004331","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.688.5159","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.688.5159","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://eil.stanford.edu/publications/jinkyoo_park/IEEE_BigData2014.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.8999999761581421,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1567512734","https://openalex.org/W1571870753","https://openalex.org/W1777124189","https://openalex.org/W1943248590","https://openalex.org/W1973310094","https://openalex.org/W1983957710","https://openalex.org/W1999314995","https://openalex.org/W2000304567","https://openalex.org/W2018887192","https://openalex.org/W2041823554","https://openalex.org/W2049633694","https://openalex.org/W2092150674","https://openalex.org/W2099768828","https://openalex.org/W2101234009","https://openalex.org/W2121753122","https://openalex.org/W2134122536","https://openalex.org/W2143013621","https://openalex.org/W2163559927","https://openalex.org/W2209130348","https://openalex.org/W2616570347","https://openalex.org/W6637968757","https://openalex.org/W6640543372","https://openalex.org/W6674989108","https://openalex.org/W6675354045"],"related_works":["https://openalex.org/W1968523686","https://openalex.org/W566010457","https://openalex.org/W2600092203","https://openalex.org/W4293503520","https://openalex.org/W4300066510","https://openalex.org/W2056958800","https://openalex.org/W2803685231","https://openalex.org/W3134152097","https://openalex.org/W4311388919","https://openalex.org/W2966696655"],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,84],"machine":[3,24,132],"automation":[4],"and":[5,29,34],"sensing":[6],"technology":[7],"offer":[8],"new":[9],"opportunities":[10],"for":[11,42],"continuous":[12],"condition":[13],"monitoring":[14,25,118],"of":[15,46,115],"an":[16,22,38,70,122],"operating":[17],"machine.":[18,49],"This":[19,50],"paper":[20],"describes":[21],"intelligent":[23],"framework":[26,119],"that":[27,67],"integrates":[28],"utilizes":[30],"data":[31],"collection,":[32],"management,":[33],"analytics":[35],"to":[36,120,126,131],"derive":[37],"adaptive":[39],"predictive":[40],"model":[41,51,125],"the":[43,86,104,113,116,128],"energy":[44,88,123,129],"usage":[45],"a":[47,55,63,79,133],"milling":[48],"is":[52,62,90],"designed":[53],"using":[54,103],"Gaussian":[56,81,105],"Process":[57,82],"(GP)":[58],"regression":[59,65],"algorithm,":[60],"which":[61,85],"flexible":[64],"method":[66],"also":[68],"provides":[69],"uncertainty":[71],"estimate.":[72],"To":[73],"improve":[74],"computational":[75],"efficiency,":[76],"we":[77,111],"propose":[78],"Collective":[80],"(CGP)":[83],"overall":[87],"prediction":[89,124],"made":[91],"by":[92,98],"constructing":[93],"local":[94],"GP":[95],"models":[96],"weighted":[97],"probability":[99],"distribution":[100],"functions":[101],"obtained":[102],"Mixture":[106],"Model":[107],"(GMM)":[108],"technique.":[109],"Finally,":[110],"demonstrate":[112],"ability":[114],"proposed":[117],"construct":[121],"predict":[127],"used":[130],"part.":[134]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":14},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":5}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}