{"id":"https://openalex.org/W1502394320","doi":"https://doi.org/10.3968/j.pam.1925252820120302.1255","title":"On the Power Effi ciency of Artificial Neural Network (ANN) and the Classical Regression Model","display_name":"On the Power Effi ciency of Artificial Neural Network (ANN) and the Classical Regression Model","publication_year":2012,"publication_date":"2012-01-01","ids":{"openalex":"https://openalex.org/W1502394320","doi":"https://doi.org/10.3968/j.pam.1925252820120302.1255","mag":"1502394320"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.919.489","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.919.489","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cscanada.net/index.php/pam/article/download/j.pam.1925252820120302.1255/2545/","raw_type":"text"},"parent_works":[],"lineage":["https://openalex.org/W1502394320"],"child_works_count":0,"type":"article","is_traditional":true,"indexed_in":[],"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/A5081071011","display_name":"Angela Unna Chukwu","orcid":"https://orcid.org/0000-0001-5596-573X","observed_orcids":["https://orcid.org/0000-0001-5596-573X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Angela Chukwu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5078130109","display_name":"Kazeem A. Adepoju","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kazeem A. Adepoju","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":0.2557,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.54290822,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":96},"biblio":{"volume":"3","issue":"2","first_page":"28","last_page":"34"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9951000213623047,"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/T10320","display_name":"Neural Networks and Applications","score":0.9951000213623047,"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/T12676","display_name":"Machine Learning and ELM","score":0.0019000000320374966,"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/T13141","display_name":"Statistical Methods and Applications","score":0.00039999998989515007,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"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":0.9980000257492065},{"id":"https://openalex.org/keywords/model-efficiency-comparison","display_name":"model efficiency comparison","score":0.6629999876022339},{"id":"https://openalex.org/keywords/transfer-function","display_name":"transfer function","score":0.9629999995231628},{"id":"https://openalex.org/keywords/variance-estimation","display_name":"variance estimation","score":0.9879999756813049},{"id":"https://openalex.org/keywords/prediction-error","display_name":"prediction error","score":0.5630000233650208}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7500724792480469},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5892372727394104},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5725327730178833},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5530958771705627},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5076984167098999},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45087406039237976},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4256803095340729},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4101177453994751},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3144834041595459},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.30474379658699036},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2663796544075012},{"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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.919.489","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.919.489","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cscanada.net/index.php/pam/article/download/j.pam.1925252820120302.1255/2545/","raw_type":"text"},{"id":"mag:1502394320","doi":"https://doi.org/10.3968/j.pam.1925252820120302.1255","is_oa":false,"landing_page_url":"http://www.cscanada.net/index.php/pam/article/view/2474","pdf_url":null,"source":{"id":"https://openalex.org/S2764892492","display_name":"Progress in applied mathematics","issn_l":"1925-251X","issn":["1925-251X"],"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":"Progress in applied mathematics","raw_type":null},{"id":"mag:3151832019","doi":null,"is_oa":false,"landing_page_url":"http://www.cscanada.net/index.php/pam/article/download/j.pam.1925252820120302.1255/2545","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"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":6,"referenced_works":["https://openalex.org/W2009004702","https://openalex.org/W2091020207","https://openalex.org/W2112688502","https://openalex.org/W2137983211","https://openalex.org/W2325530759","https://openalex.org/W2732998557"],"related_works":["https://openalex.org/W1490710791","https://openalex.org/W1607453716","https://openalex.org/W3010099657","https://openalex.org/W3165564345","https://openalex.org/W2922207210","https://openalex.org/W4285780497","https://openalex.org/W2794147945","https://openalex.org/W3127060194","https://openalex.org/W18851843","https://openalex.org/W2110340087"],"abstract_inverted_index":{"This":[0],"research":[1],"work":[2],"presents":[3],"new":[4],"development":[5],"in":[6,58],"the":[7,18,54,59,62,67,79,87],"field":[8],"of":[9,20,27,56,64,90],"natural":[10],"science,":[11],"where":[12],"comparison":[13],"is":[14,49,100],"made":[15],"theoretically":[16],"on":[17,43,61],"efficiency":[19,63,77],"both":[21],"classical":[22],"regression":[23,69,81],"models":[24,82],"and":[25,93],"that":[26,47,86],"artificial":[28],"neural":[29],"network":[30],"models,":[31],"with":[32,53],"various":[33],"transfer":[34],"functions":[35],"without":[36],"data":[37],"consideration.":[38],"The":[39,71],"results":[40,55],"obtained":[41],"based":[42],"variance":[44],"estimation":[45],"indicates":[46],"ANN":[48,65,76],"better":[50],"which":[51],"coincides":[52],"Authors":[57],"past":[60],"over":[66,78],"traditional":[68],"models.":[70],"certain":[72],"conditions":[73],"required":[74],"for":[75],"conventional":[80],"were":[83],"noted":[84],"only":[85],"optimal":[88],"number":[89],"hidden":[91],"layers":[92],"neurons":[94],"needed":[95],"to":[96,103],"achieve":[97],"minimum":[98],"error":[99],"still":[101],"open":[102],"further":[104],"investigation.":[105],"Key":[108],"words:":[109]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2013,"cited_by_count":1}],"updated_date":"2026-11-14T11:04:58.165337","created_date":"2016-06-24T00:00:00"}