{"id":"https://openalex.org/W1988980086","doi":"https://doi.org/10.1142/s0218213001000593","title":"A NOVEL NEURAL-WAVELET DIAGNOSTICS APPROACH: APPLICATION TO MAGNETIC FLOWMETER","display_name":"A NOVEL NEURAL-WAVELET DIAGNOSTICS APPROACH: APPLICATION TO MAGNETIC FLOWMETER","publication_year":2001,"publication_date":"2001-09-01","ids":{"openalex":"https://openalex.org/W1988980086","doi":"https://doi.org/10.1142/s0218213001000593","mag":"1988980086"},"language":"en","primary_location":{"id":"doi:10.1142/s0218213001000593","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218213001000593","pdf_url":null,"source":{"id":"https://openalex.org/S178780388","display_name":"International Journal of Artificial Intelligence Tools","issn_l":"0218-2130","issn":["0218-2130","1793-6349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal on Artificial Intelligence Tools","raw_type":"journal-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/A5023736025","display_name":"Rui Gao","orcid":"https://orcid.org/0000-0002-3599-7678"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"R. GAO","raw_affiliation_strings":["Applied Intelligent Systems Lab, Purdue University, 1290 NUCL, W. Lafayette, IN 47907-1290, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Applied Intelligent Systems Lab, Purdue University, 1290 NUCL, W. Lafayette, IN 47907-1290, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026343641","display_name":"E. Eryurek","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"E. ERYUREK","raw_affiliation_strings":["Applied Intelligent Systems Lab, Purdue University, 1290 NUCL, W. Lafayette, IN 47907-1290, USA","Fisher-Rosemount, 12001 Technology Drive, Eden Prairie, MN 5535-3695, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Applied Intelligent Systems Lab, Purdue University, 1290 NUCL, W. Lafayette, IN 47907-1290, USA","institution_ids":[]},{"raw_affiliation_string":"Fisher-Rosemount, 12001 Technology Drive, Eden Prairie, MN 5535-3695, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076719857","display_name":"Lefteri H. Tsoukalas","orcid":"https://orcid.org/0000-0002-6718-1163"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"L. H. TSOUKALAS","raw_affiliation_strings":["Applied Intelligent Systems Lab, Purdue University, 1290 NUCL, W. Lafayette, IN 47907-1290, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Applied Intelligent Systems Lab, Purdue University, 1290 NUCL, W. Lafayette, IN 47907-1290, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3577,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.66640697,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":"03","first_page":"421","last_page":"429"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12537","display_name":"Flow Measurement and Analysis","score":0.9925000071525574,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/T11778","display_name":"Electrical and Bioimpedance Tomography","score":0.9866999983787537,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8304735422134399},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.6103233098983765},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6098663806915283},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5903200507164001},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4776019752025604},{"id":"https://openalex.org/keywords/flow-measurement","display_name":"Flow measurement","score":0.4640687108039856},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.435549795627594},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.42068421840667725},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4199671149253845},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32080262899398804}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8304735422134399},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6103233098983765},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6098663806915283},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5903200507164001},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4776019752025604},{"id":"https://openalex.org/C16302685","wikidata":"https://www.wikidata.org/wiki/Q15091623","display_name":"Flow measurement","level":2,"score":0.4640687108039856},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.435549795627594},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.42068421840667725},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4199671149253845},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32080262899398804},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218213001000593","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218213001000593","pdf_url":null,"source":{"id":"https://openalex.org/S178780388","display_name":"International Journal of Artificial Intelligence Tools","issn_l":"0218-2130","issn":["0218-2130","1793-6349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal on Artificial Intelligence Tools","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5699999928474426,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":2,"referenced_works":["https://openalex.org/W1980149518","https://openalex.org/W2152328854"],"related_works":["https://openalex.org/W2382174632","https://openalex.org/W2129959498","https://openalex.org/W2784060934","https://openalex.org/W2902714807","https://openalex.org/W2537489131","https://openalex.org/W2394084632","https://openalex.org/W2373379180","https://openalex.org/W2377868609","https://openalex.org/W4214727124","https://openalex.org/W2114443143"],"abstract_inverted_index":{"Magnetic":[0],"flow":[1,11],"meters":[2],"(magmeters)":[3],"are":[4,28,42],"instruments":[5],"for":[6,67],"measuring":[7],"the":[8,48,101],"velocity":[9],"of":[10,50,100],"in":[12,33,53,59,73],"many":[13],"industrial":[14],"applications.":[15],"The":[16,94],"signal":[17],"that":[18],"comes":[19],"from":[20],"a":[21,79],"magmeter":[22,60],"is":[23,87],"noisy":[24,74],"and":[25,56,70,97,107],"conventional":[26,113],"approaches":[27],"often":[29],"not":[30],"effective":[31],"enough":[32],"dealing":[34],"with":[35],"actual":[36],"field":[37],"noise.":[38],"Furthermore,":[39],"diagnostic":[40],"functions":[41],"attracting":[43],"increasing":[44],"attention,":[45],"due":[46],"to":[47,89,109,112],"possibility":[49],"implementing":[51],"them":[52],"an":[54],"inexpensive":[55],"reliable":[57],"manner":[58],"hardware.":[61],"Neural":[62],"networks":[63,86],"have":[64],"proven":[65],"capabilities":[66],"both":[68],"learning":[69],"data":[71],"handling":[72],"circumstances.":[75],"In":[76],"this":[77],"paper,":[78],"novel":[80],"approach":[81,103],"based":[82],"on":[83],"wavelet":[84],"neural":[85],"presented":[88],"attack":[90],"these":[91],"two":[92],"objectives.":[93],"stability,":[95],"accuracy":[96],"response":[98],"time":[99],"new":[102],"has":[104],"been":[105],"tested,":[106],"found":[108],"be":[110],"superior":[111],"approaches.":[114]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}