{"id":"https://openalex.org/W2087937959","doi":"https://doi.org/10.1109/hpcs.2010.5547061","title":"Calculating the impact factor of neural networks on optimization algorithm for sensor selection","display_name":"Calculating the impact factor of neural networks on optimization algorithm for sensor selection","publication_year":2010,"publication_date":"2010-06-01","ids":{"openalex":"https://openalex.org/W2087937959","doi":"https://doi.org/10.1109/hpcs.2010.5547061","mag":"2087937959"},"language":"en","primary_location":{"id":"doi:10.1109/hpcs.2010.5547061","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpcs.2010.5547061","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 International Conference on High Performance Computing & Simulation","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/A5051062621","display_name":"Abdolhossein Alipoor","orcid":null},"institutions":[{"id":"https://openalex.org/I155419210","display_name":"Islamic Azad University, Science and Research Branch","ror":"https://ror.org/03187yj51","country_code":"IR","type":"education","lineage":["https://openalex.org/I110525433","https://openalex.org/I155419210"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Abdolhossein Alipoor","raw_affiliation_strings":["CE Department, Science and Research Branch, Islamic Azad University, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"CE Department, Science and Research Branch, Islamic Azad University, Tehran, Iran","institution_ids":["https://openalex.org/I155419210"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051470844","display_name":"Touraj Banirostam","orcid":"https://orcid.org/0000-0002-3477-9046"},"institutions":[{"id":"https://openalex.org/I155419210","display_name":"Islamic Azad University, Science and Research Branch","ror":"https://ror.org/03187yj51","country_code":"IR","type":"education","lineage":["https://openalex.org/I110525433","https://openalex.org/I155419210"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Touraj Banirostam","raw_affiliation_strings":["CE Department, Science and Research Branch, Islamic Azad University, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"CE Department, Science and Research Branch, Islamic Azad University, Tehran, Iran","institution_ids":["https://openalex.org/I155419210"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013148342","display_name":"Mehdi N. Fesharaki","orcid":null},"institutions":[{"id":"https://openalex.org/I78323350","display_name":"Malek Ashtar University of Technology","ror":"https://ror.org/0043ezw98","country_code":"IR","type":"education","lineage":["https://openalex.org/I78323350"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mehdi N. Fesharaki","raw_affiliation_strings":["CE Department, Malek Ashtar University, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"CE Department, Malek Ashtar University, Tehran, Iran","institution_ids":["https://openalex.org/I78323350"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5051062621"],"corresponding_institution_ids":["https://openalex.org/I155419210"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12566886,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"5","issue":null,"first_page":"650","last_page":"655"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9986000061035156,"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":0.9986000061035156,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9908999800682068,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9878000020980835,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7757748365402222},{"id":"https://openalex.org/keywords/fitness-function","display_name":"Fitness function","score":0.7312825918197632},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.6949142217636108},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6882405281066895},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5299139022827148},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.47011223435401917},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4666483402252197},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.44964537024497986},{"id":"https://openalex.org/keywords/time-delay-neural-network","display_name":"Time delay neural network","score":0.43700259923934937},{"id":"https://openalex.org/keywords/computational-intelligence","display_name":"Computational intelligence","score":0.43603214621543884},{"id":"https://openalex.org/keywords/radial-basis-function","display_name":"Radial basis function","score":0.42709171772003174},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.393795907497406},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3436512351036072},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32777106761932373}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7757748365402222},{"id":"https://openalex.org/C176066374","wikidata":"https://www.wikidata.org/wiki/Q629118","display_name":"Fitness function","level":3,"score":0.7312825918197632},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.6949142217636108},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6882405281066895},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5299139022827148},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.47011223435401917},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4666483402252197},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.44964537024497986},{"id":"https://openalex.org/C175202392","wikidata":"https://www.wikidata.org/wiki/Q2434543","display_name":"Time delay neural network","level":3,"score":0.43700259923934937},{"id":"https://openalex.org/C139502532","wikidata":"https://www.wikidata.org/wiki/Q1122090","display_name":"Computational intelligence","level":2,"score":0.43603214621543884},{"id":"https://openalex.org/C98856871","wikidata":"https://www.wikidata.org/wiki/Q1588488","display_name":"Radial basis function","level":3,"score":0.42709171772003174},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.393795907497406},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3436512351036072},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32777106761932373}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/hpcs.2010.5547061","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpcs.2010.5547061","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 International Conference on High Performance Computing & Simulation","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":14,"referenced_works":["https://openalex.org/W1495021568","https://openalex.org/W1899646986","https://openalex.org/W1984692084","https://openalex.org/W1992428130","https://openalex.org/W2012451526","https://openalex.org/W2057037490","https://openalex.org/W2105845337","https://openalex.org/W2109364787","https://openalex.org/W2115998527","https://openalex.org/W2116892496","https://openalex.org/W2131711034","https://openalex.org/W3012317737","https://openalex.org/W4212997115","https://openalex.org/W6639743027"],"related_works":["https://openalex.org/W2990957018","https://openalex.org/W4249380586","https://openalex.org/W2496186792","https://openalex.org/W960661091","https://openalex.org/W2275065097","https://openalex.org/W2157934879","https://openalex.org/W2597186421","https://openalex.org/W1540849649","https://openalex.org/W2284565437","https://openalex.org/W2605112186"],"abstract_inverted_index":{"Intelligent":[0],"sensor":[1,29,162],"selection":[2,30],"for":[3,149,167],"monitoring":[4],"operations":[5],"is":[6,61,163],"one":[7],"of":[8,45,58,97,108,141,160],"the":[9,42,48,70,94,139],"serious":[10],"subjects":[11],"to":[12,25,92],"reduce":[13],"information":[14,19],"processing":[15],"time":[16,199],"and":[17,36,119,134,165,197],"increase":[18],"fusion":[20],"accuracy.":[21],"This":[22,39],"paper":[23],"attempts":[24],"design":[26],"an":[27,90],"intelligent":[28],"service":[31,40],"by":[32],"using":[33,184],"optimization":[34,59],"algorithm":[35,133,190],"neural":[37,87,109,168,186],"networks.":[38],"specifies":[41],"best":[43],"group":[44],"sensors":[46,152],"having":[47],"highest":[49],"recognition":[50,158,194],"rate":[51,159],"in":[52,66,73,100,153,178,188],"each":[53,98,161],"situation.":[54],"The":[55],"important":[56],"part":[57],"algorithms":[60],"their":[62,136],"fitness":[63,82,95],"function.":[64],"Since":[65],"this":[67,104],"problem,":[68],"unlike":[69],"problems":[71],"explained":[72],"[1,":[74],"2]":[75],"we":[76,84,181],"can":[77],"not":[78],"extract":[79],"a":[80,86,131],"mathematical":[81],"function,":[83],"use":[85],"network":[88,110,121,187],"as":[89],"estimator":[91],"evaluate":[93],"value":[96],"chromosome":[99],"genetic":[101,132,142,189],"algorithm.":[102,143],"In":[103],"paper,":[105],"three":[106,126,174],"types":[107],"including":[111],"Multilayer":[112],"Perceptron":[113],"(MLP),":[114],"Radial":[115],"Basis":[116],"function":[117],"(RBF)":[118],"ELMAN":[120],"are":[122,128],"used.":[123],"Then":[124,156],"these":[125],"networks":[127,169],"performed":[129],"within":[130],"compare":[135],"influence":[137],"on":[138],"result":[140],"We":[144],"define":[145],"500":[146],"various":[147],"scenarios":[148,176],"6":[150],"different":[151,175],"several":[154],"conditions.":[155],"object":[157,193],"calculated":[164],"used":[166],"training":[170],"process.":[171],"After":[172],"running":[173],"separately":[177],"10":[179],"times,":[180],"found":[182],"that":[183],"MLP":[185],"has":[191],"maximum":[192],"rate,":[195],"97.6%":[196],"minimum":[198],"consuming,":[200],"22":[201],"seconds.":[202]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}