{"id":"https://openalex.org/W2934768696","doi":"https://doi.org/10.1109/access.2019.2908385","title":"Soft Measurement for VFA Concentration in Anaerobic Digestion for Treating Kitchen Waste Based on Improved DBN","display_name":"Soft Measurement for VFA Concentration in Anaerobic Digestion for Treating Kitchen Waste Based on Improved DBN","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2934768696","doi":"https://doi.org/10.1109/access.2019.2908385","mag":"2934768696"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2908385","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2908385","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08678631.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08678631.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039821809","display_name":"Yuhong Wang","orcid":"https://orcid.org/0000-0001-8881-1067"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhong Wang","raw_affiliation_strings":["College of Information and Control Engineering, China University of Petroleum, Qingdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information and Control Engineering, China University of Petroleum, Qingdao, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079571659","display_name":"Xiaohui Li","orcid":"https://orcid.org/0000-0002-7821-8849"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohui Li","raw_affiliation_strings":["College of Information and Control Engineering, China University of Petroleum, Qingdao, China"],"raw_orcid":"https://orcid.org/0000-0002-7821-8849","affiliations":[{"raw_affiliation_string":"College of Information and Control Engineering, China University of Petroleum, Qingdao, China","institution_ids":["https://openalex.org/I4210162190"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210162190"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.2707,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.84763612,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"7","issue":null,"first_page":"60931","last_page":"60939"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9994000196456909,"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/T12676","display_name":"Machine Learning and ELM","score":0.9994000196456909,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9879000186920166,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T12697","display_name":"Water Quality Monitoring Technologies","score":0.9814000129699707,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.6837418675422668},{"id":"https://openalex.org/keywords/anaerobic-digestion","display_name":"Anaerobic digestion","score":0.6773765087127686},{"id":"https://openalex.org/keywords/deep-belief-network","display_name":"Deep belief network","score":0.5735228061676025},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5241565704345703},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.4929177761077881},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48504871129989624},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.45767471194267273},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.452846884727478},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41094279289245605},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3629950284957886},{"id":"https://openalex.org/keywords/process-engineering","display_name":"Process engineering","score":0.33384013175964355},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16092848777770996},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.14134320616722107}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6837418675422668},{"id":"https://openalex.org/C499616599","wikidata":"https://www.wikidata.org/wiki/Q555853","display_name":"Anaerobic digestion","level":3,"score":0.6773765087127686},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.5735228061676025},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5241565704345703},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.4929177761077881},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48504871129989624},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.45767471194267273},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.452846884727478},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41094279289245605},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3629950284957886},{"id":"https://openalex.org/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","level":1,"score":0.33384013175964355},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16092848777770996},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.14134320616722107},{"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/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C516920438","wikidata":"https://www.wikidata.org/wiki/Q37129","display_name":"Methane","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2908385","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2908385","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08678631.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:49a85fb2f86e4530a09d843e3b568f73","is_oa":true,"landing_page_url":"https://doaj.org/article/49a85fb2f86e4530a09d843e3b568f73","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 60931-60939 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2908385","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2908385","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08678631.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2934768696.pdf","grobid_xml":"https://content.openalex.org/works/W2934768696.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W1608547086","https://openalex.org/W1990741916","https://openalex.org/W1991666844","https://openalex.org/W1993882792","https://openalex.org/W2007221293","https://openalex.org/W2009086942","https://openalex.org/W2019779527","https://openalex.org/W2026131661","https://openalex.org/W2086750735","https://openalex.org/W2100495367","https://openalex.org/W2106324246","https://openalex.org/W2120390927","https://openalex.org/W2136922672","https://openalex.org/W2165021685","https://openalex.org/W2353350139","https://openalex.org/W2393222755","https://openalex.org/W2477325593","https://openalex.org/W2573526403","https://openalex.org/W2612051854","https://openalex.org/W2750690746","https://openalex.org/W4312861447","https://openalex.org/W6629510986","https://openalex.org/W6705377908","https://openalex.org/W6737758492","https://openalex.org/W6743504269"],"related_works":["https://openalex.org/W1530536511","https://openalex.org/W2585432886","https://openalex.org/W2165991108","https://openalex.org/W3082895349","https://openalex.org/W2565516711","https://openalex.org/W3004069267","https://openalex.org/W4327774331","https://openalex.org/W3136021864","https://openalex.org/W2572334665","https://openalex.org/W2248239756"],"abstract_inverted_index":{"Anaerobic":[0],"digestion":[1,33],"is":[2,52,67,78,89,100,123,161],"a":[3,42,97,105,150],"new":[4],"method":[5,45,160],"for":[6,146],"treating":[7],"kitchen":[8,30],"waste,":[9,13],"which":[10,88],"can":[11],"reduce":[12],"protect":[14],"the":[15,22,55,62,70,82,86,118,136,142],"environment,":[16],"and":[17,102,110,167],"create":[18],"clean":[19],"energy.":[20],"Because":[21],"concentration":[23],"of":[24,57,72,85,129],"volatile":[25],"fatty":[26],"acids":[27],"(VFA)":[28],"in":[29,38],"waste":[31],"anaerobic":[32],"process":[34],"cannot":[35],"be":[36],"measured":[37],"real":[39,98],"time":[40],"online,":[41],"soft":[43,151],"measurement":[44,56,152],"based":[46],"on":[47],"deep":[48],"belief":[49],"network":[50,119],"(DBN)":[51],"applied":[53,68],"to":[54,69,80,125,132,148],"VFA.":[58],"In":[59],"this":[60,159],"paper,":[61],"extreme":[63,143],"learning":[64,76,144],"machine":[65,145],"(ELM)":[66],"training":[71,117,147],"DBN.":[73],"The":[74,94,154],"adaptive":[75],"rate":[77],"introduced":[79],"increase":[81],"convergence":[83],"speed":[84],"network,":[87],"different":[90],"from":[91,96],"traditional":[92,165],"DBF.":[93],"data":[95,131],"plant":[99],"classified":[101],"decomposed":[103],"using":[104],"Gaussian":[106],"mixture":[107],"model":[108],"(GMM)":[109],"ensemble":[111],"empirical":[112],"mode":[113],"analysis":[114,128],"(EEMD)":[115],"before":[116],"firstly.":[120],"A":[121],"DBN":[122,169],"used":[124],"perform":[126],"numerical":[127],"original":[130],"extract":[133],"features.":[134],"Then,":[135],"extracted":[137],"features":[138],"are":[139],"input":[140],"into":[141],"obtain":[149],"model.":[153,170],"experimental":[155],"verification":[156],"shows":[157],"that":[158],"more":[162],"precise":[163],"than":[164],"methods":[166],"pure":[168]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}