{"id":"https://openalex.org/W2539555599","doi":"https://doi.org/10.1109/iske.2010.5680791","title":"The study of robust design GLM of second-order response surface in noise factors","display_name":"The study of robust design GLM of second-order response surface in noise factors","publication_year":2010,"publication_date":"2010-11-01","ids":{"openalex":"https://openalex.org/W2539555599","doi":"https://doi.org/10.1109/iske.2010.5680791","mag":"2539555599"},"language":"en","primary_location":{"id":"doi:10.1109/iske.2010.5680791","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iske.2010.5680791","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","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/A5101951825","display_name":"Sumei Zhang","orcid":"https://orcid.org/0000-0002-0459-6126"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Sumei Zhang","raw_affiliation_strings":["Department of applied mathematics, School of science, Xi''an University of Posts and Telecommunications, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Department of applied mathematics, School of science, Xi''an University of Posts and Telecommunications, Xi'an, China","institution_ids":["https://openalex.org/I4210136859"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101951825"],"corresponding_institution_ids":["https://openalex.org/I4210136859"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.40295342,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":"31","issue":null,"first_page":"43","last_page":"45"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11798","display_name":"Optimal Experimental Design Methods","score":0.9987999796867371,"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":0.9987999796867371,"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":0.9934999942779541,"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/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9876999855041504,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.7041891813278198},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.565245509147644},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4641467332839966},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.46064215898513794},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.45757174491882324},{"id":"https://openalex.org/keywords/least-squares-function-approximation","display_name":"Least-squares function approximation","score":0.4552350342273712},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.4449971616268158},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4399607181549072},{"id":"https://openalex.org/keywords/generalized-least-squares","display_name":"Generalized least squares","score":0.4381883144378662},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4160740375518799},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3792632222175598},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3741036057472229},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.16434767842292786}],"concepts":[{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.7041891813278198},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.565245509147644},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4641467332839966},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.46064215898513794},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.45757174491882324},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.4552350342273712},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.4449971616268158},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4399607181549072},{"id":"https://openalex.org/C188649462","wikidata":"https://www.wikidata.org/wiki/Q2246261","display_name":"Generalized least squares","level":3,"score":0.4381883144378662},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4160740375518799},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3792632222175598},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3741036057472229},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.16434767842292786},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iske.2010.5680791","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iske.2010.5680791","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","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":11,"referenced_works":["https://openalex.org/W1528905581","https://openalex.org/W1976474629","https://openalex.org/W1985845039","https://openalex.org/W2084607915","https://openalex.org/W2084651859","https://openalex.org/W2104167971","https://openalex.org/W2147530768","https://openalex.org/W2166920652","https://openalex.org/W4236852734","https://openalex.org/W4247116797","https://openalex.org/W4301861531"],"related_works":["https://openalex.org/W2034819163","https://openalex.org/W2167126078","https://openalex.org/W4319880936","https://openalex.org/W2797020683","https://openalex.org/W1959514624","https://openalex.org/W4250719734","https://openalex.org/W2065890685","https://openalex.org/W4380487384","https://openalex.org/W2123913166","https://openalex.org/W2171417898"],"abstract_inverted_index":{"The":[0,23,84],"purpose":[1],"of":[2,25,60,75,103],"this":[3],"paper":[4,95],"was":[5,32,51],"to":[6],"provide":[7],"a":[8,35,73],"method":[9],"for":[10],"disposing":[11],"response":[12,77],"surface":[13,78],"with":[14],"residual":[15],"error":[16],"heterogeneity":[17],"by":[18,53,56,65,88],"accommodating":[19],"generalized":[20],"linear":[21,58],"modeling.":[22],"approach":[24],"Jan":[26],"Engel":[27],"and":[28,101],"A.":[29],"Freek":[30],"Huele":[31],"taken":[33],"as":[34,41],"starting":[36],"point,":[37],"treating":[38],"noise":[39,61,70,80],"variance":[40],"fixed":[42],"effects.":[43],"It":[44],"was,":[45],"however,":[46],"assumed":[47],"that":[48],"process":[49],"variability":[50],"caused":[52],"not":[54],"only":[55],"the":[57,66,94,97],"effects":[59,68],"factors":[62,81],"but":[63],"also":[64],"reaction":[67],"between":[69],"factors.":[71],"Therefore,":[72],"model":[74,85],"second-order":[76],"in":[79],"is":[82,86],"established.":[83],"fitted":[87],"iteratively":[89],"reweighted":[90],"least":[91],"squares.":[92],"Moreover,":[93],"discusses":[96],"model's":[98],"statistics":[99],"analysis":[100],"test":[102],"hypothesis.":[104]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}