{"id":"https://openalex.org/W7152610340","doi":"https://doi.org/10.1109/icecet63943.2025.11472541","title":"AI-Driven Performance Prediction of Centrifugal Pumps Operating in Parallel Using an Artificial Neural Network Model","display_name":"AI-Driven Performance Prediction of Centrifugal Pumps Operating in Parallel Using an Artificial Neural Network Model","publication_year":2025,"publication_date":"2025-07-03","ids":{"openalex":"https://openalex.org/W7152610340","doi":"https://doi.org/10.1109/icecet63943.2025.11472541"},"language":null,"primary_location":{"id":"doi:10.1109/icecet63943.2025.11472541","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icecet63943.2025.11472541","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 5th International Conference on Electrical, Computer and Energy Technologies (ICECET)","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/A5022521494","display_name":"Miniyenkosi Ngcukayitobi","orcid":null},"institutions":[{"id":"https://openalex.org/I165390105","display_name":"University of South Africa","ror":"https://ror.org/048cwvf49","country_code":"ZA","type":"education","lineage":["https://openalex.org/I165390105"]}],"countries":["ZA"],"is_corresponding":true,"raw_author_name":"Miniyenkosi Ngcukayitobi","raw_affiliation_strings":["University of South Africa (Unisa),Deparment of Mechanical, Bioresources, and Biomedical Engineering,Johannesburg,South Africa"],"affiliations":[{"raw_affiliation_string":"University of South Africa (Unisa),Deparment of Mechanical, Bioresources, and Biomedical Engineering,Johannesburg,South Africa","institution_ids":["https://openalex.org/I165390105"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5022521494"],"corresponding_institution_ids":["https://openalex.org/I165390105"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.71454265,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13050","display_name":"Oil and Gas Production Techniques","score":0.12120000272989273,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T13050","display_name":"Oil and Gas Production Techniques","score":0.12120000272989273,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T11202","display_name":"Cavitation Phenomena in Pumps","score":0.0754999965429306,"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/T11372","display_name":"Hydraulic and Pneumatic Systems","score":0.06419999897480011,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/artificial-neural-network","display_name":"Artificial neural network","score":0.6672999858856201},{"id":"https://openalex.org/keywords/performance-prediction","display_name":"Performance prediction","score":0.5672000050544739},{"id":"https://openalex.org/keywords/centrifugal-pump","display_name":"Centrifugal pump","score":0.5385000109672546},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.2870999872684479},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.24529999494552612}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6672999858856201},{"id":"https://openalex.org/C2777115002","wikidata":"https://www.wikidata.org/wiki/Q7168246","display_name":"Performance prediction","level":2,"score":0.5672000050544739},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5662000179290771},{"id":"https://openalex.org/C166675230","wikidata":"https://www.wikidata.org/wiki/Q627111","display_name":"Centrifugal pump","level":3,"score":0.5385000109672546},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3368000090122223},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.33239999413490295},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3188000023365021},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.2870999872684479},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.24529999494552612},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.22380000352859497}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icecet63943.2025.11472541","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icecet63943.2025.11472541","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 5th International Conference on Electrical, Computer and Energy Technologies (ICECET)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.8430856466293335}],"awards":[],"funders":[{"id":"https://openalex.org/F4320324956","display_name":"University of South Africa","ror":"https://ror.org/048cwvf49"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2058715873","https://openalex.org/W2802765905","https://openalex.org/W4212857766","https://openalex.org/W4247780392","https://openalex.org/W4386323891","https://openalex.org/W4400129113","https://openalex.org/W4402594102","https://openalex.org/W4405240276"],"related_works":[],"abstract_inverted_index":{"Centrifugal":[0],"pumps":[1,38],"play":[2],"a":[3,71,78,86],"crucial":[4],"role":[5],"in":[6,31,40,106,120,130],"various":[7],"industries,":[8],"necessitating":[9],"efficient":[10],"monitoring":[11],"and":[12,17,49,85,99,126],"optimization":[13],"to":[14,69],"enhance":[15],"performance":[16,62],"reliability.":[18],"This":[19],"study":[20],"evaluates":[21],"the":[22,33,60,103,114],"application":[23],"of":[24,36,83,88,116],"an":[25],"Artificial":[26],"Neural":[27],"Network":[28],"(ANN)":[29],"model":[30],"predicting":[32],"overall":[34],"efficiency":[35,57],"centrifugal":[37],"operating":[39],"parallel.":[41],"Three":[42],"key":[43],"parameters":[44],"(working":[45],"pressure,":[46],"connected":[47],"pumps,":[48],"flow":[50],"rate)":[51],"were":[52],"used":[53],"as":[54,59],"inputs,":[55],"with":[56],"serving":[58],"primary":[61],"indicator.":[63],"The":[64],"optimal":[65],"ANN":[66,97],"architecture,":[67],"determined":[68],"be":[70],"3-16-1":[72],"configuration,":[73],"minimized":[74],"prediction":[75],"error,":[76],"achieving":[77],"validation":[79],"R<sup":[80,89],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[81,90],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[82,91],"0.99752":[84],"testing":[87],"0.99951.":[92],"A":[93],"strong":[94],"correlation":[95],"between":[96],"predictions":[98],"experimental":[100],"data":[101],"confirms":[102],"model\u2019s":[104],"effectiveness":[105],"accurately":[107],"estimating":[108],"pump":[109,122],"efficiency.":[110],"These":[111],"findings":[112],"highlight":[113],"potential":[115],"AI-driven":[117],"predictive":[118],"models":[119],"improving":[121],"performance,":[123],"reducing":[124],"downtime,":[125],"optimizing":[127],"energy":[128],"consumption":[129],"industrial":[131],"applications.":[132]},"counts_by_year":[],"updated_date":"2026-04-11T06:13:24.991567","created_date":"2026-04-10T00:00:00"}