{"id":"https://openalex.org/W2461508386","doi":"https://doi.org/10.1080/03610918.2015.1018999","title":"Using orthogonal array for constructing three-level search designs","display_name":"Using orthogonal array for constructing three-level search designs","publication_year":2015,"publication_date":"2015-11-13","ids":{"openalex":"https://openalex.org/W2461508386","doi":"https://doi.org/10.1080/03610918.2015.1018999","mag":"2461508386"},"language":"en","primary_location":{"id":"doi:10.1080/03610918.2015.1018999","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2015.1018999","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","raw_type":"journal-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/A5059518895","display_name":"Nabaz Esmailzadeh","orcid":"https://orcid.org/0000-0002-5797-3204"},"institutions":[{"id":"https://openalex.org/I3124704065","display_name":"University of Kurdistan","ror":"https://ror.org/04k89yk85","country_code":"IR","type":"education","lineage":["https://openalex.org/I3124704065"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Nabaz Esmailzadeh","raw_affiliation_strings":["Department of Statistics, University of Kurdistan, Sanandaj, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of Kurdistan, Sanandaj, Iran","institution_ids":["https://openalex.org/I3124704065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066164563","display_name":"Zahra Zandi","orcid":"https://orcid.org/0000-0002-1910-450X"},"institutions":[{"id":"https://openalex.org/I3124704065","display_name":"University of Kurdistan","ror":"https://ror.org/04k89yk85","country_code":"IR","type":"education","lineage":["https://openalex.org/I3124704065"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Zahra Zandi","raw_affiliation_strings":["Department of Statistics, University of Kurdistan, Sanandaj, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of Kurdistan, Sanandaj, Iran","institution_ids":["https://openalex.org/I3124704065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5059518895"],"corresponding_institution_ids":["https://openalex.org/I3124704065"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.25534616,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"46","issue":"3","first_page":"1906","last_page":"1917"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11798","display_name":"Optimal Experimental Design Methods","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11798","display_name":"Optimal Experimental Design Methods","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9563999772071838,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.9334999918937683,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/orthogonal-array","display_name":"Orthogonal array","score":0.8576898574829102},{"id":"https://openalex.org/keywords/fractional-factorial-design","display_name":"Fractional factorial design","score":0.6351227760314941},{"id":"https://openalex.org/keywords/orthographic-projection","display_name":"Orthographic projection","score":0.6170647144317627},{"id":"https://openalex.org/keywords/design-of-experiments","display_name":"Design of experiments","score":0.5439860224723816},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.5100863575935364},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.45785602927207947},{"id":"https://openalex.org/keywords/factorial","display_name":"Factorial","score":0.45247143507003784},{"id":"https://openalex.org/keywords/factorial-experiment","display_name":"Factorial experiment","score":0.4486624002456665},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43074238300323486},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4220939874649048},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20259660482406616},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1967257857322693},{"id":"https://openalex.org/keywords/taguchi-methods","display_name":"Taguchi methods","score":0.11755448579788208}],"concepts":[{"id":"https://openalex.org/C42632107","wikidata":"https://www.wikidata.org/wiki/Q2031860","display_name":"Orthogonal array","level":3,"score":0.8576898574829102},{"id":"https://openalex.org/C16469947","wikidata":"https://www.wikidata.org/wiki/Q2400745","display_name":"Fractional factorial design","level":3,"score":0.6351227760314941},{"id":"https://openalex.org/C175694140","wikidata":"https://www.wikidata.org/wiki/Q980329","display_name":"Orthographic projection","level":2,"score":0.6170647144317627},{"id":"https://openalex.org/C34559072","wikidata":"https://www.wikidata.org/wiki/Q2334061","display_name":"Design of experiments","level":2,"score":0.5439860224723816},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.5100863575935364},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45785602927207947},{"id":"https://openalex.org/C183763347","wikidata":"https://www.wikidata.org/wiki/Q120976","display_name":"Factorial","level":2,"score":0.45247143507003784},{"id":"https://openalex.org/C169222746","wikidata":"https://www.wikidata.org/wiki/Q4116558","display_name":"Factorial experiment","level":2,"score":0.4486624002456665},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43074238300323486},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4220939874649048},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20259660482406616},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1967257857322693},{"id":"https://openalex.org/C83469408","wikidata":"https://www.wikidata.org/wiki/Q2036525","display_name":"Taguchi methods","level":2,"score":0.11755448579788208},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/03610918.2015.1018999","is_oa":false,"landing_page_url":"https://doi.org/10.1080/03610918.2015.1018999","pdf_url":null,"source":{"id":"https://openalex.org/S153329750","display_name":"Communications in Statistics - Simulation and Computation","issn_l":"0361-0918","issn":["0361-0918","1532-4141"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Communications in Statistics - Simulation and Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W193474163","https://openalex.org/W1988803919","https://openalex.org/W1997543254","https://openalex.org/W2030450921","https://openalex.org/W2039177656","https://openalex.org/W2087252774","https://openalex.org/W2154592744"],"related_works":["https://openalex.org/W2407556212","https://openalex.org/W1966613695","https://openalex.org/W112270409","https://openalex.org/W4205438635","https://openalex.org/W2024402881","https://openalex.org/W2729256625","https://openalex.org/W1553990698","https://openalex.org/W3023579313","https://openalex.org/W2355578312","https://openalex.org/W2081064647"],"abstract_inverted_index":{"We":[0],"consider":[1],"the":[2,54,72,82],"problem":[3],"of":[4,16,40],"constructing":[5],"search":[6,22,36],"designs":[7,23,37,62],"for":[8,26],"3m":[9],"factorial":[10],"designs.":[11],"By":[12],"using":[13],"projection":[14],"properties":[15],"some":[17,21],"three-level":[18],"orthogonal":[19,35,74],"arrays,":[20],"are":[24,38],"obtained":[25,34],"3":[27],"\u2a7d":[28,30],"m":[29],"11.":[31],"The":[32,60],"new":[33],"capable":[39],"searching":[41,66,81],"and":[42,49,57],"identifying":[43],"up":[44],"to":[45],"four":[46],"two-factor":[47],"interactions":[48],"estimating":[50],"them":[51],"along":[52],"with":[53],"general":[55],"mean":[56],"main":[58],"effects.":[59,84],"resulted":[61],"have":[63,77],"very":[64],"high":[65,78],"probabilities;":[67],"it":[68],"means":[69],"that":[70],"besides":[71],"well-known":[73],"structure,":[75],"they":[76],"ability":[79],"in":[80],"true":[83]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
