{"id":"https://openalex.org/W3145537777","doi":"https://doi.org/10.1109/iccad.2010.5653959","title":"Fidelity metrics for estimation models","display_name":"Fidelity metrics for estimation models","publication_year":2010,"publication_date":"2010-11-01","ids":{"openalex":"https://openalex.org/W3145537777","doi":"https://doi.org/10.1109/iccad.2010.5653959","mag":"3145537777"},"language":"en","primary_location":{"id":"doi:10.1109/iccad.2010.5653959","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad.2010.5653959","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5035736924","display_name":"Haris Javaid","orcid":"https://orcid.org/0009-0008-3472-0803"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Haris Javaid","raw_affiliation_strings":["School of Computer Science and Engineering, University of New South Wales, Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, University of New South Wales, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077613152","display_name":"Aleksander Ignjatovic","orcid":null},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Aleksander Ignjatovic","raw_affiliation_strings":["School of Computer Science and Engineering, University of New South Wales, Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, University of New South Wales, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030042327","display_name":"Sri Parameswaran","orcid":"https://orcid.org/0000-0003-0435-9080"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Sri Parameswaran","raw_affiliation_strings":["School of Computer Science and Engineering, University of New South Wales, Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, University of New South Wales, Sydney, Australia","institution_ids":["https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I31746571"],"apc_list":null,"apc_paid":null,"fwci":0.8773,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.74084402,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"16","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T11159","display_name":"Manufacturing Process and Optimization","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.9979000091552734,"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":0.6484313607215881},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.6055682897567749},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5286034941673279},{"id":"https://openalex.org/keywords/mean-absolute-percentage-error","display_name":"Mean absolute percentage error","score":0.5008604526519775},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5001957416534424},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.48889556527137756},{"id":"https://openalex.org/keywords/approximation-error","display_name":"Approximation error","score":0.4880615472793579},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.48661455512046814},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.47798651456832886},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.45987242460250854},{"id":"https://openalex.org/keywords/multiprocessing","display_name":"Multiprocessing","score":0.4551723599433899},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.37658506631851196},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30364730954170227},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2423035204410553},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23773613572120667},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.13137418031692505},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.11690440773963928}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6484313607215881},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.6055682897567749},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5286034941673279},{"id":"https://openalex.org/C150217764","wikidata":"https://www.wikidata.org/wiki/Q6803607","display_name":"Mean absolute percentage error","level":3,"score":0.5008604526519775},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5001957416534424},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.48889556527137756},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.4880615472793579},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.48661455512046814},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.47798651456832886},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.45987242460250854},{"id":"https://openalex.org/C4822641","wikidata":"https://www.wikidata.org/wiki/Q846651","display_name":"Multiprocessing","level":2,"score":0.4551723599433899},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.37658506631851196},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30364730954170227},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2423035204410553},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23773613572120667},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.13137418031692505},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.11690440773963928},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccad.2010.5653959","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccad.2010.5653959","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1966835268","https://openalex.org/W2057934400","https://openalex.org/W2078483536","https://openalex.org/W2097197938","https://openalex.org/W2102679547","https://openalex.org/W2104822358","https://openalex.org/W2106872673","https://openalex.org/W2124536457","https://openalex.org/W2126431245","https://openalex.org/W2137362862","https://openalex.org/W2153041769","https://openalex.org/W2158382962","https://openalex.org/W2802553787","https://openalex.org/W3143298614","https://openalex.org/W4249472430","https://openalex.org/W4250908292"],"related_works":["https://openalex.org/W2381850946","https://openalex.org/W4380449851","https://openalex.org/W3125091513","https://openalex.org/W4360987692","https://openalex.org/W3200959266","https://openalex.org/W2087911819","https://openalex.org/W1978221571","https://openalex.org/W2136152605","https://openalex.org/W4386935599","https://openalex.org/W2258403645"],"abstract_inverted_index":{"Estimation":[0],"models":[1,17,33,43],"play":[2],"a":[3,62,169,174,179,184,195,201,259,273],"vital":[4],"role":[5],"in":[6,20,57,94,119,123,240],"many":[7],"aspects":[8],"of":[9,25,30,41,64,69,77,84,115,145,171,181,231,246,275],"day":[10,12],"to":[11,45,111,150,153,166,205,262,284],"life.":[13],"Extremely":[14],"complex":[15],"estimation":[16,32,59,71,117,198,203,220,252,264,287],"are":[18,130,142],"employed":[19],"the":[21,28,38,42,75,78,82,85,97,104,113,146,156,213,218,224,243,250],"design":[22,124,241],"space":[23,125],"exploration":[24],"SoCs,":[26],"and":[27,81,200,209,227,233],"efficacy":[29],"these":[31],"is":[34],"usually":[35],"measured":[36],"by":[37,279],"absolute":[39,50,98,215,229,270,281],"error":[40,51,230],"compared":[44,211],"known":[46,135],"actual":[47,86],"results.":[48],"Such":[49],"based":[52,131],"metrics":[53,110,162,191],"can":[54,236],"often":[55],"result":[56],"over-designed":[58,286],"models,":[60],"with":[61,266],"number":[63],"researchers":[65],"suggesting":[66],"that":[67,249],"fidelity":[68,114,161,190,245,274],"an":[70,116,263,285],"model":[72,199,204,253,260,265],"(correlation":[73],"between":[74],"ordering":[76,83],"estimated":[79],"points":[80,154],"points)":[87],"should":[88],"be":[89,237,256],"examined":[90],"instead":[91],"of,":[92],"or":[93,268],"addition":[95],"to,":[96],"error.":[99,216],"In":[100],"this":[101],"paper,":[102],"for":[103,121,194],"first":[105,128,147],"time,":[106],"we":[107],"propose":[108],"four":[109],"measure":[112],"model,":[118,221],"particular":[120],"use":[122],"exploration.":[126],"The":[127,139,159,188],"two":[129,133,141,148],"on":[132],"well":[134],"rank":[136],"correlation":[137,177],"coefficients.":[138],"other":[140],"weighted":[143],"versions":[144],"metrics,":[149],"give":[151],"importance":[152],"nearer":[155],"Pareto":[157],"front.":[158],"proposed":[160,189],"range":[163],"from":[164],"-1":[165,182],"1,":[167],"where":[168],"value":[170,180],"1":[172],"reflects":[173,183],"perfect":[175,185],"positive":[176],"while":[178],"negative":[186],"correlation.":[187],"were":[192,210],"calculated":[193],"single":[196],"processor":[197],"multiprocessor":[202,219,251],"observe":[206],"their":[207],"behavior,":[208],"against":[212],"models'":[214],"For":[217],"even":[222],"though":[223],"worst":[225,244],"average":[226],"maximum":[228],"6.40%":[232],"16.61%":[234],"respectively":[235],"considered":[238],"reasonable":[239],"automation,":[242],"0.753":[247],"suggests":[248],"may":[254],"not":[255],"as":[257,277],"good":[258],"(compared":[261],"same":[267],"higher":[269],"errors":[271],"but":[272],"0.95)":[276],"depicted":[278],"its":[280],"accuracy,":[282],"leading":[283],"model.":[288]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
