{"id":"https://openalex.org/W1538214331","doi":null,"title":"Application Concept of Artificial Neural Networks for Turbomachinery Design","display_name":"Application Concept of Artificial Neural Networks for Turbomachinery Design","publication_year":2009,"publication_date":"2009-01-01","ids":{"openalex":"https://openalex.org/W1538214331","mag":"1538214331"},"language":"en","primary_location":{"id":"pmh:oai:doaj.org/article:d109941077c445f697a969480ed7f37e","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/d109941077c445f697a969480ed7f37e","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,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computer Assisted Methods in Engineering and Science, Vol 16, Iss 2 (2017)","raw_type":"article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["doaj"],"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/A5031134973","display_name":"Mark Azzam","orcid":"https://orcid.org/0000-0003-4914-3371","observed_orcids":["https://orcid.org/0000-0003-4914-3371"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mark Azzam","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-4914-3371","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034452332","display_name":"J.-Ch. Haag","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jan-Christoph Haag","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5012756311","display_name":"Peter Jeschke","orcid":"https://orcid.org/0000-0002-6369-093X","observed_orcids":["https://orcid.org/0000-0002-6369-093X","https://orcid.org/0000-0001-7853-3534"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peter Jeschke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":95},"biblio":{"volume":"16","issue":"2","first_page":"143","last_page":"160"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10944","display_name":"Turbomachinery Performance and Optimization","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10944","display_name":"Turbomachinery Performance and Optimization","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10320","display_name":"Neural Networks and Applications","score":0.00019999999494757503,"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/T13954","display_name":"Aerospace Engineering and Applications","score":9.999999747378752e-05,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":1.0},{"id":"https://openalex.org/keywords/turbomachinery-design","display_name":"turbomachinery design","score":0.9810000061988831},{"id":"https://openalex.org/keywords/axial-compressor","display_name":"axial compressor","score":0.9779999852180481},{"id":"https://openalex.org/keywords/compressor-map","display_name":"compressor map","score":0.6919999718666077},{"id":"https://openalex.org/keywords/mean-line-analysis","display_name":"mean-line analysis","score":0.7369999885559082},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.8069999814033508},{"id":"https://openalex.org/keywords/data-normalization","display_name":"data normalization","score":0.8870000243186951}],"concepts":[{"id":"https://openalex.org/C200398353","wikidata":"https://www.wikidata.org/wiki/Q63973","display_name":"Turbomachinery","level":2,"score":0.9143444895744324},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7677077054977417},{"id":"https://openalex.org/C131097465","wikidata":"https://www.wikidata.org/wiki/Q178898","display_name":"Gas compressor","level":2,"score":0.610973596572876},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5105506181716919},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5072231292724609},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4469984471797943},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43584948778152466},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.43467479944229126},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.42553412914276123},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.20981544256210327},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2076413333415985}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:doaj.org/article:d109941077c445f697a969480ed7f37e","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/d109941077c445f697a969480ed7f37e","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,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computer Assisted Methods in Engineering and Science, Vol 16, Iss 2 (2017)","raw_type":"article"},{"id":"pmh:oai:publications.rwth-aachen.de:193043","doi":null,"is_oa":false,"landing_page_url":"http://publications.rwth-aachen.de/record/193043","pdf_url":null,"source":{"id":"https://openalex.org/S4306401033","display_name":"RWTH Publications (RWTH Aachen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I887968799","host_organization_name":"RWTH Aachen University","host_organization_lineage":["https://openalex.org/I887968799"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computer assisted mechanics and engineering sciences 16(2), 143-160 (2009).","raw_type":"info:eu-repo/semantics/article"},{"id":"mag:1538214331","doi":null,"is_oa":false,"landing_page_url":"https://cames.ippt.gov.pl/index.php/cames/article/download/158/141","pdf_url":null,"source":{"id":"https://openalex.org/S2764722602","display_name":"Computer Assisted Mechanics and Engineering Sciences","issn_l":"1232-308X","issn":["1232-308X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Computer Assisted Mechanics and Engineering Sciences","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W206058477","https://openalex.org/W268958618","https://openalex.org/W398979332","https://openalex.org/W430486651","https://openalex.org/W1525050871","https://openalex.org/W1533618852","https://openalex.org/W1545745553","https://openalex.org/W1554663460","https://openalex.org/W1663973292","https://openalex.org/W1912576785","https://openalex.org/W1973631422","https://openalex.org/W2005799258","https://openalex.org/W2006165205","https://openalex.org/W2040870580","https://openalex.org/W2073155105","https://openalex.org/W2084719216","https://openalex.org/W2088669839","https://openalex.org/W2113553269","https://openalex.org/W2119479037","https://openalex.org/W2293184016","https://openalex.org/W2325219351","https://openalex.org/W3015571647","https://openalex.org/W3105196959"],"related_works":["https://openalex.org/W4381185204","https://openalex.org/W2032448552","https://openalex.org/W7222956141","https://openalex.org/W4360904239","https://openalex.org/W2123125996","https://openalex.org/W2182863118","https://openalex.org/W4283784997","https://openalex.org/W4200056038","https://openalex.org/W4390063247","https://openalex.org/W2113553269"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"the":[3,12,42,52,78,88,97,104,109,118,128,152,156,173],"results":[4,178],"of":[5,14,26,64,70,90,108,117,122,136,172],"an":[6,133,160],"extensive":[7],"investigation":[8],"evaluating":[9],"and":[10,82,140,155,168,191],"improving":[11],"development":[13,67],"artificial":[15],"neural":[16],"network":[17,83],"(ANN)":[18],"models":[19,187],"for":[20,188],"turbomachinery":[21,189],"design":[22,190],"purposes.":[23],"A":[24],"set":[25],"1100":[27],"differing":[28],"axial":[29],"compressor":[30,36,54],"geometries":[31],"based":[32],"on":[33],"5":[34],"single-stage":[35],"rigs":[37],"was":[38,143],"prepared.":[39],"Computations":[40],"with":[41,113,132],"mean":[43,115],"line":[44],"analysis":[45,192],"tool":[46],"AXIAL\u2122":[47],"took":[48],"place":[49],"to":[50,102,145,184],"determine":[51],"according":[53],"maps":[55],"defined":[56],"by":[57,150],"15":[58],"operating":[59],"points":[60],"each.":[61],"The":[62,124,138,162,177],"challenge":[63],"ANN":[65],"model":[66,99,126,142],"in":[68,170],"terms":[69],"dimensionality":[71],"reduction":[72],"(feature":[73],"selection),":[74],"data":[75,158],"normalization,":[76],"defining":[77],"networks":[79],"necessary":[80],"plasticity,":[81],"training":[84],"is":[85,100],"discussed":[86],"using":[87],"example":[89],"three":[91],"different":[92],"models.":[93],"As":[94],"a":[95,114],"result,":[96],"first":[98],"able":[101],"predict":[103,146],"total":[105,129],"pressure":[106,130],"loss":[107],"rotor":[110],"blade":[111],"row":[112],"magnitude":[116],"relative":[119],"error":[120],"(MMRE)":[121],"3.6%.":[123],"second":[125],"predicts":[127],"ratio":[131],"average":[134],"accuracy":[135],"0.8%.":[137],"third":[139],"last":[141],"trained":[144],"basic":[147],"geometrical":[148],"parameters":[149],"presenting":[151],"load":[153],"level":[154],"performance":[157],"as":[159],"input.":[161],"achieved":[163],"MMRE":[164],"varied":[165],"between":[166],"2.4%":[167],"5.6%":[169],"respect":[171],"particular":[174],"output":[175],"variable.":[176],"show":[179],"that":[180],"ANNs":[181],"are":[182],"applicable":[183],"develop":[185],"efficient":[186],"purposes,":[193],"respectively.":[194]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2013,"cited_by_count":2}],"updated_date":"2026-10-27T15:51:10.671819","created_date":"2016-06-24T00:00:00"}
