{"id":"https://openalex.org/W2092116787","doi":"https://doi.org/10.1109/icnc.2014.6975830","title":"Incorporating the multiple linear regression with the neural network to the form design of product image","display_name":"Incorporating the multiple linear regression with the neural network to the form design of product image","publication_year":2014,"publication_date":"2014-08-01","ids":{"openalex":"https://openalex.org/W2092116787","doi":"https://doi.org/10.1109/icnc.2014.6975830","mag":"2092116787"},"language":"en","primary_location":{"id":"doi:10.1109/icnc.2014.6975830","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc.2014.6975830","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 10th International Conference on Natural Computation (ICNC)","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/A5103129583","display_name":"Hung-Yuan Chen","orcid":"https://orcid.org/0000-0002-8537-0582"},"institutions":[{"id":"https://openalex.org/I92582371","display_name":"Southern Taiwan University of Science and Technology","ror":"https://ror.org/0029n1t76","country_code":"TW","type":"education","lineage":["https://openalex.org/I92582371"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hung-Yuan Chen","raw_affiliation_strings":["Department of Visual Communication Design, Southern Taiwan University of Science and Technology, Tainan, Taiwan, ROC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Visual Communication Design, Southern Taiwan University of Science and Technology, Tainan, Taiwan, ROC","institution_ids":["https://openalex.org/I92582371"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103073741","display_name":"Yu-Ming Chang","orcid":"https://orcid.org/0000-0003-2461-5061"},"institutions":[{"id":"https://openalex.org/I92582371","display_name":"Southern Taiwan University of Science and Technology","ror":"https://ror.org/0029n1t76","country_code":"TW","type":"education","lineage":["https://openalex.org/I92582371"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yu-Ming Chang","raw_affiliation_strings":["Department of Creative Product Design, Southern Taiwan University of Science and Technology, Tainan, Taiwan, ROC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Creative Product Design, Southern Taiwan University of Science and Technology, Tainan, Taiwan, ROC","institution_ids":["https://openalex.org/I92582371"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I92582371"],"apc_list":null,"apc_paid":null,"fwci":0.6203,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.71957672,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"41","issue":null,"first_page":"174","last_page":"180"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12496","display_name":"Color perception and design","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12496","display_name":"Color perception and design","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12032","display_name":"Multisensory perception and integration","score":0.9686999917030334,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12114","display_name":"Sensory Analysis and Statistical Methods","score":0.9678000211715698,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6835416555404663},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.6757656335830688},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6028538942337036},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.5791674852371216},{"id":"https://openalex.org/keywords/product-design","display_name":"Product design","score":0.5593680739402771},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5385341048240662},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.49048539996147156},{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.4753013551235199},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4561362564563751},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4528827965259552},{"id":"https://openalex.org/keywords/new-product-development","display_name":"New product development","score":0.4164980947971344},{"id":"https://openalex.org/keywords/industrial-engineering","display_name":"Industrial engineering","score":0.3867985010147095},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3806818127632141},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3579323887825012},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3309556841850281},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.22184139490127563},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1689860224723816},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09984534978866577}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6835416555404663},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.6757656335830688},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6028538942337036},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.5791674852371216},{"id":"https://openalex.org/C120823896","wikidata":"https://www.wikidata.org/wiki/Q1043226","display_name":"Product design","level":3,"score":0.5593680739402771},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5385341048240662},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.49048539996147156},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.4753013551235199},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4561362564563751},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4528827965259552},{"id":"https://openalex.org/C19351080","wikidata":"https://www.wikidata.org/wiki/Q1395034","display_name":"New product development","level":2,"score":0.4164980947971344},{"id":"https://openalex.org/C13736549","wikidata":"https://www.wikidata.org/wiki/Q4489420","display_name":"Industrial engineering","level":1,"score":0.3867985010147095},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3806818127632141},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3579323887825012},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3309556841850281},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.22184139490127563},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1689860224723816},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09984534978866577},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","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},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icnc.2014.6975830","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc.2014.6975830","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 10th International Conference on Natural Computation (ICNC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1965060776","https://openalex.org/W1966672363","https://openalex.org/W1970290536","https://openalex.org/W1982948794","https://openalex.org/W1985871142","https://openalex.org/W1999209397","https://openalex.org/W1999729226","https://openalex.org/W2000561090","https://openalex.org/W2004295879","https://openalex.org/W2013367930","https://openalex.org/W2017916616","https://openalex.org/W2019133978","https://openalex.org/W2036913038","https://openalex.org/W2037389284","https://openalex.org/W2042532697","https://openalex.org/W2045454048","https://openalex.org/W2049404550","https://openalex.org/W2060549586","https://openalex.org/W2130294528","https://openalex.org/W2136459883","https://openalex.org/W3143764655","https://openalex.org/W4205209088","https://openalex.org/W6680332796","https://openalex.org/W6829473730"],"related_works":["https://openalex.org/W31220157","https://openalex.org/W2198164489","https://openalex.org/W2028624523","https://openalex.org/W1969426912","https://openalex.org/W2079825352","https://openalex.org/W3144360982","https://openalex.org/W1968930765","https://openalex.org/W2288557197","https://openalex.org/W4233024177","https://openalex.org/W2814492520"],"abstract_inverted_index":{"A":[0],"consumers'":[1],"psychological":[2],"perception":[3],"(CPP)":[4],"of":[5,25,52,63,72,81,97,109,138],"a":[6,18,26,36,42,79],"product":[7,15,48,53,148],"is":[8,131,142],"induced":[9],"by":[10],"its":[11],"appearance,":[12],"and":[13,76,92],"thereby":[14],"form":[16],"plays":[17],"vital":[19],"role":[20],"for":[21],"the":[22,56,61,64,70,86,89,93,98,105,111,122,128,136,139],"commercial":[23],"success":[24],"product.":[27],"This":[28],"study":[29,68],"proposes":[30],"an":[31,73,134],"incorporated":[32,65],"design":[33,57,71],"approach":[34,141],"combining":[35],"multiple":[37],"linear":[38],"regression":[39],"technique":[40],"with":[41,121],"back-propagation":[43],"neural":[44],"network":[45],"to":[46,84,103,114,145],"aid":[47],"designers":[49],"incorporate":[50],"CPPs":[51],"forms":[54],"in":[55,119],"process.":[58],"To":[59],"demonstrate":[60],"feasibility":[62],"approach,":[66],"this":[67],"considers":[69],"automobile":[74,90,116,124,129],"profile":[75,91,117,125,130],"then":[77],"performs":[78],"series":[80],"evaluation":[82,99],"trials":[83,100],"establish":[85],"relationship":[87],"between":[88],"CPPs.":[94],"The":[95],"results":[96],"are":[101],"used":[102],"construct":[104],"MLRBPN":[106],"models":[107],"capable":[108],"predicting":[110],"likely":[112],"CPP":[113],"any":[115],"designed":[118],"accordance":[120],"numerical":[123],"definition.":[126],"Although":[127],"chosen":[132],"as":[133],"example,":[135],"concept":[137],"proposed":[140],"equally":[143],"applicable":[144],"other":[146],"consumer":[147],"form.":[149]},"counts_by_year":[{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
