{"id":"https://openalex.org/W2548883732","doi":"https://doi.org/10.1109/iske.2010.5680809","title":"Study on least trimmed squares fuzzy neural networks","display_name":"Study on least trimmed squares fuzzy neural networks","publication_year":2010,"publication_date":"2010-11-01","ids":{"openalex":"https://openalex.org/W2548883732","doi":"https://doi.org/10.1109/iske.2010.5680809","mag":"2548883732"},"language":"en","primary_location":{"id":"doi:10.1109/iske.2010.5680809","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iske.2010.5680809","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/A5061259618","display_name":"Hsu-Kun Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I142974352","display_name":"National Sun Yat-sen University","ror":"https://ror.org/00mjawt10","country_code":"TW","type":"education","lineage":["https://openalex.org/I142974352"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Hsu-Kun Wu","raw_affiliation_strings":["Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan","institution_ids":["https://openalex.org/I142974352"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111452632","display_name":"Jer\u2010Guang Hsieh","orcid":null},"institutions":[{"id":"https://openalex.org/I98298690","display_name":"I-Shou University","ror":"https://ror.org/04d7e4m76","country_code":"TW","type":"education","lineage":["https://openalex.org/I98298690"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jer-Guang Hsieh","raw_affiliation_strings":["Department of Electrical Engineering, I-Shou University, Kaohsiung, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, I-Shou University, Kaohsiung, Taiwan","institution_ids":["https://openalex.org/I98298690"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101942691","display_name":"Ker\u2010Wei Yu","orcid":"https://orcid.org/0000-0002-9760-3822"},"institutions":[{"id":"https://openalex.org/I43518871","display_name":"National Kaohsiung Marine University","ror":"https://ror.org/00ca6fy54","country_code":"TW","type":"education","lineage":["https://openalex.org/I43518871"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ker-Wei Yu","raw_affiliation_strings":["Department of Marine Engineering, National Kaohsiung Marine University, Kaohsiung, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Marine Engineering, National Kaohsiung Marine University, Kaohsiung, Taiwan","institution_ids":["https://openalex.org/I43518871"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5061259618"],"corresponding_institution_ids":["https://openalex.org/I142974352"],"apc_list":null,"apc_paid":null,"fwci":1.3531,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.85800937,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"123","last_page":"127"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9948999881744385,"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":0.9948999881744385,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9934999942779541,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9879999756813049,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7552312612533569},{"id":"https://openalex.org/keywords/least-trimmed-squares","display_name":"Least trimmed squares","score":0.7101302742958069},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6691919565200806},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6005997657775879},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5449139475822449},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5263869762420654},{"id":"https://openalex.org/keywords/robust-regression","display_name":"Robust regression","score":0.5173627734184265},{"id":"https://openalex.org/keywords/iteratively-reweighted-least-squares","display_name":"Iteratively reweighted least squares","score":0.5167459845542908},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.500328779220581},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.4709041118621826},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.46726006269454956},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.4430024027824402},{"id":"https://openalex.org/keywords/least-squares-function-approximation","display_name":"Least-squares function approximation","score":0.4401324987411499},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3937924802303314},{"id":"https://openalex.org/keywords/non-linear-least-squares","display_name":"Non-linear least squares","score":0.38042598962783813},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30283766984939575},{"id":"https://openalex.org/keywords/explained-sum-of-squares","display_name":"Explained sum of squares","score":0.1391100287437439},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1069178581237793}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7552312612533569},{"id":"https://openalex.org/C25294789","wikidata":"https://www.wikidata.org/wiki/Q6510410","display_name":"Least trimmed squares","level":4,"score":0.7101302742958069},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6691919565200806},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6005997657775879},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5449139475822449},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5263869762420654},{"id":"https://openalex.org/C70259352","wikidata":"https://www.wikidata.org/wiki/Q1847839","display_name":"Robust regression","level":3,"score":0.5173627734184265},{"id":"https://openalex.org/C126090379","wikidata":"https://www.wikidata.org/wiki/Q6094424","display_name":"Iteratively reweighted least squares","level":4,"score":0.5167459845542908},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.500328779220581},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.4709041118621826},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.46726006269454956},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4430024027824402},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.4401324987411499},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3937924802303314},{"id":"https://openalex.org/C45923927","wikidata":"https://www.wikidata.org/wiki/Q3319230","display_name":"Non-linear least squares","level":3,"score":0.38042598962783813},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30283766984939575},{"id":"https://openalex.org/C49847556","wikidata":"https://www.wikidata.org/wiki/Q3964631","display_name":"Explained sum of squares","level":2,"score":0.1391100287437439},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1069178581237793},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iske.2010.5680809","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iske.2010.5680809","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":[{"id":"https://openalex.org/F4320321040","display_name":"National Science Council","ror":"https://ror.org/02kv4zf79"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W93985499","https://openalex.org/W149129625","https://openalex.org/W1534675906","https://openalex.org/W1553483187","https://openalex.org/W2002041997","https://openalex.org/W2005656886","https://openalex.org/W2012712694","https://openalex.org/W2024000733","https://openalex.org/W2046033161","https://openalex.org/W2101036899","https://openalex.org/W2116798985","https://openalex.org/W2119926576","https://openalex.org/W2124202921","https://openalex.org/W2128266155","https://openalex.org/W2129249398","https://openalex.org/W2144242878","https://openalex.org/W2146225536","https://openalex.org/W2149668177","https://openalex.org/W2166813136","https://openalex.org/W2320553484","https://openalex.org/W2947321605","https://openalex.org/W3044681081","https://openalex.org/W4205806204","https://openalex.org/W4210306310","https://openalex.org/W4255230573","https://openalex.org/W4285719527","https://openalex.org/W4292283308","https://openalex.org/W6781003217"],"related_works":["https://openalex.org/W1809551201","https://openalex.org/W2105166836","https://openalex.org/W2006385744","https://openalex.org/W3000904183","https://openalex.org/W2137798711","https://openalex.org/W4387810207","https://openalex.org/W1500807766","https://openalex.org/W343746398","https://openalex.org/W4226047642","https://openalex.org/W2387920592"],"abstract_inverted_index":{"In":[0],"this":[1,100],"paper,":[2],"least":[3,63],"trimmed":[4],"squares":[5,64],"(LTS)":[6],"estimators,":[7],"frequently":[8],"used":[9],"in":[10,99],"robust":[11],"(or":[12],"resistant)":[13],"linear":[14],"parametric":[15],"regression":[16,29],"problems,":[17],"will":[18,67,73],"be":[19,68,74],"generalized":[20],"to":[21,76],"nonparametric":[22],"LTS-fuzzy":[23],"neural":[24,85],"networks":[25,86],"(LTS-FNNs)":[26],"for":[27,82],"nonlinear":[28,49],"problems.":[30,51],"Emphasis":[31],"is":[32],"put":[33],"particularly":[34],"on":[35,57],"the":[36,78,89,96],"robustness":[37,79,104],"against":[38,80,105],"outliers.":[39,106],"This":[40],"provides":[41],"alternative":[42],"learning":[43,50],"machines":[44],"when":[45],"faced":[46],"with":[47],"general":[48],"Simple":[52],"weight":[53],"updating":[54],"rules":[55],"based":[56],"gradient":[58],"descent":[59],"and":[60,88],"iteratively":[61],"reweighted":[62],"(IRLS)":[65],"algorithms":[66],"provided.":[69],"Some":[70],"numerical":[71],"examples":[72],"provided":[75],"compare":[77],"outliers":[81],"usual":[83],"fuzzy":[84],"(FNNs)":[87],"proposed":[90,98],"LTS-FNNs.":[91],"Simulation":[92],"results":[93],"show":[94],"that":[95],"LTS-FNNs":[97],"paper":[101],"have":[102],"good":[103]},"counts_by_year":[{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
