{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T10:59:19Z","timestamp":1783421959328,"version":"3.54.6"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"33","license":[{"start":{"date-parts":[[2024,8,15]],"date-time":"2024-08-15T00:00:00Z","timestamp":1723680000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,8,15]],"date-time":"2024-08-15T00:00:00Z","timestamp":1723680000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61671099"],"award-info":[{"award-number":["61671099"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2024,11]]},"DOI":"10.1007\/s00521-024-10328-6","type":"journal-article","created":{"date-parts":[[2024,8,15]],"date-time":"2024-08-15T19:02:06Z","timestamp":1723748526000},"page":"20699-20710","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Intuitionistic fuzzy broad learning system with a new non-membership function"],"prefix":"10.1007","volume":"36","author":[{"given":"Mengying","family":"Jiang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7394-7295","authenticated-orcid":false,"given":"Huisheng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuxuan","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,8,15]]},"reference":[{"issue":"2","key":"10328_CR1","doi-asserted-by":"publisher","first-page":"464","DOI":"10.1109\/72.991432","volume":"13","author":"C Lin","year":"2002","unstructured":"Lin C, Wang S (2002) Fuzzy support vector machines. IEEE Trans Neural Netw 13(2):464\u2013471","journal-title":"IEEE Trans Neural Netw"},{"key":"10328_CR2","doi-asserted-by":"publisher","first-page":"268","DOI":"10.1007\/s00521-006-0028-z","volume":"15","author":"X Jiang","year":"2006","unstructured":"Jiang X, Yi Z, Lv JC (2006) Fuzzy SVM with a new fuzzy membership function. Neural Comput Appl 15:268\u2013276. https:\/\/doi.org\/10.1007\/s00521-006-0028-z","journal-title":"Neural Comput Appl"},{"key":"10328_CR3","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1016\/j.neucom.2012.11.023","volume":"110","author":"W An","year":"2013","unstructured":"An W, Liang M (2013) Fuzzy support vector machine based on within-class scatter for classification problems with outliers or noises. Neurocomputing 110:101\u2013110. https:\/\/doi.org\/10.1016\/j.neucom.2012.11.023","journal-title":"Neurocomputing"},{"issue":"3","key":"10328_CR4","doi-asserted-by":"publisher","first-page":"558","DOI":"10.1109\/TFUZZ.2010.2042721","volume":"18","author":"R Batuwita","year":"2010","unstructured":"Batuwita R, Palade V (2010) FSVM-CIL: fuzzy support vector machines for class imbalance learning. IEEE Trans Fuzzy Syst 18(3):558\u2013571","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"10328_CR5","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2023.3296503","author":"Z Liang","year":"2023","unstructured":"Liang Z, Ding S (2023) Fuzzy Twin Support Vector Machines with Distribution Inputs. IEEE Trans Fuzzy Syst. https:\/\/doi.org\/10.1109\/TFUZZ.2023.3296503","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"7","key":"10328_CR6","doi-asserted-by":"publisher","first-page":"448","DOI":"10.1049\/el.2012.3642","volume":"49","author":"W Zhang","year":"2013","unstructured":"Zhang W, Ji H (2013) Fuzzy extreme learning machine for classification. Electron Lett 49(7):448\u2013450","journal-title":"Electron Lett"},{"key":"10328_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2023.102150","author":"TY Yin","year":"2024","unstructured":"Yin TY, Chen HM, Wan JH (2024) Exploiting feature multi-correlations for multilabel feature selection in robust multi-neighborhood fuzzy $$\\beta $$ covering space. Inf Fusion. https:\/\/doi.org\/10.1016\/j.inffus.2023.102150","journal-title":"Inf Fusion"},{"issue":"12","key":"10328_CR8","doi-asserted-by":"publisher","first-page":"4516","DOI":"10.1109\/TFUZZ.2023.3287193","volume":"31","author":"TY Yin","year":"2023","unstructured":"Yin TY, Chen HM (2023) A Robust Multilabel Feature Selection Approach Based on Graph Structure Considering Fuzzy Dependency and Feature Interaction. IEEE Trans Fuzzy Syst 31(12):4516\u20134528. https:\/\/doi.org\/10.1109\/TFUZZ.2023.3287193","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"10328_CR9","first-page":"225","volume":"3","author":"MH Ha","year":"2011","unstructured":"Ha MH, Huang S, Wang C, Wang XL (2011) Intuitionistic fuzzy support vector machine. J Hebei Univ (Nat Sci Ed) 3:225\u2013229","journal-title":"J Hebei Univ (Nat Sci Ed)"},{"key":"10328_CR10","doi-asserted-by":"publisher","first-page":"635","DOI":"10.1007\/s00500-012-0937-y","volume":"17","author":"M Ha","year":"2013","unstructured":"Ha M, Wang C, Chen J (2013) The support vector machine based on intuitionistic fuzzy number and kernel function. Soft Comput 17:635\u2013641. https:\/\/doi.org\/10.1007\/s00500-012-0937-y","journal-title":"Soft Comput"},{"issue":"6","key":"10328_CR11","doi-asserted-by":"publisher","first-page":"1536","DOI":"10.1109\/TFUZZ.2017.2752138","volume":"25","author":"Y Tian","year":"2017","unstructured":"Tian Y, Sun M, Deng Z, Luo J, Li Y (2017) A new fuzzy set and nonkernel SVM approach for mislabeled binary classification with applications. IEEE Trans Fuzzy Syst 25(6):1536\u20131545","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"11","key":"10328_CR12","doi-asserted-by":"publisher","first-page":"2140","DOI":"10.1109\/TFUZZ.2019.2893863","volume":"27","author":"S Rezvani","year":"2019","unstructured":"Rezvani S, Wang X, Pourpanah F (2019) Intuitionistic fuzzy twin support vector machines. IEEE Trans Fuzzy Syst 27(11):2140\u20132151","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"10328_CR13","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-022-07655-x","author":"MA Ganaie","year":"2022","unstructured":"Ganaie MA, Kumari A, Malik AK, Tanveer M (2022) EEG signal classification using improved intuitionistic fuzzy twin support vector machines. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-022-07655-x","journal-title":"Neural Comput Appl"},{"key":"10328_CR14","doi-asserted-by":"publisher","first-page":"2701","DOI":"10.1007\/s11063-020-10222-x","volume":"51","author":"S Laxmi","year":"2020","unstructured":"Laxmi S, Gupta SK (2020) Intuitionistic fuzzy proximal support vector machines for pattern classification. Neural Process Lett 51:2701\u20132735. https:\/\/doi.org\/10.1007\/s11063-020-10222-x","journal-title":"Neural Process Lett"},{"issue":"22","key":"10328_CR15","doi-asserted-by":"publisher","first-page":"14039","DOI":"10.1007\/s00500-021-06193-3","volume":"25","author":"S Laxmi","year":"2021","unstructured":"Laxmi S, Gupta SK, Kumar S (2021) Intuitionistic fuzzy proximal support vector machine for multicategory classification problems. Soft Comput 25(22):14039\u201314057. https:\/\/doi.org\/10.1007\/s00500-021-06193-3","journal-title":"Soft Comput"},{"key":"10328_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10479-022-04626-2","volume":"2022","author":"S Laxmi","year":"2022","unstructured":"Laxmi S, Gupta SK, Kumar S (2022) Intuitionistic fuzzy least square twin support vector machines for pattern classification. Ann Oper Res 2022:1\u201350. https:\/\/doi.org\/10.1007\/s10479-022-04626-2","journal-title":"Ann Oper Res"},{"issue":"7","key":"10328_CR17","doi-asserted-by":"publisher","first-page":"4400","DOI":"10.1109\/TCYB.2022.3165879","volume":"53","author":"M Tanveer","year":"2022","unstructured":"Tanveer M, Ganaie MA, Bhattacharjee A, Lin CT (2022) Intuitionistic fuzzy weighted least squares twin SVMs. IEEE Trans Cybern 53(7):4400\u20134409","journal-title":"IEEE Trans Cybern"},{"issue":"4","key":"10328_CR18","doi-asserted-by":"publisher","first-page":"4325","DOI":"10.1007\/s11063-022-11043-w","volume":"55","author":"U Mishra","year":"2022","unstructured":"Mishra U, Gupta D, Hazarika BB (2022) An Intuitionistic Fuzzy Random Vector Functional Link Classifier. Neural Process Lett 55(4):4325\u20134346. https:\/\/doi.org\/10.1007\/s11063-022-11043-w","journal-title":"Neural Process Lett"},{"key":"10328_CR19","doi-asserted-by":"crossref","unstructured":"Malik AK, Ganaie MA, Tanveer M, Suganthan PN (2022) Alzheimer\u2019s disease diagnosis via intuitionistic fuzzy random vector functional link network. IEEE Trans Comput Soc Syst","DOI":"10.1109\/SSCI51031.2022.10022212"},{"issue":"1","key":"10328_CR20","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1109\/TNNLS.2017.2716952","volume":"29","author":"CLP Chen","year":"2018","unstructured":"Chen CLP, Liu ZL (2018) Broad learning system: an effective and efficient incremental learning system without the need for deep architecture. IEEE Trans Neural Netw Learn Syst 29(1):10\u201324","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"7","key":"10328_CR21","first-page":"267","volume":"35","author":"L Wang","year":"2019","unstructured":"Wang L, Yu Z (2019) Application of broad learning system in discrimination of mushroom toxicity. Modern Food Sci Technol 35(7):267\u2013272","journal-title":"Modern Food Sci Technol"},{"key":"10328_CR22","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1016\/j.neucom.2019.08.084","volume":"370","author":"XN Fan","year":"2019","unstructured":"Fan XN, Zhang SW (2019) LPI-BLS: Predicting lncRNA-protein interactions with a broad learning system-based stacked ensemble classifier. Neurocomputing 370:88\u201393. https:\/\/doi.org\/10.1016\/j.neucom.2019.08.084","journal-title":"Neurocomputing"},{"issue":"12","key":"10328_CR23","doi-asserted-by":"publisher","first-page":"7382","DOI":"10.1109\/TSMC.2020.2969686","volume":"51","author":"S Issa","year":"2021","unstructured":"Issa S, Peng Q, You X (2021) Emotion classification using EEG brain signals and the broad learning system. IEEE Trans Syst Man Cybern Sys 51(12):7382\u20137391","journal-title":"IEEE Trans Syst Man Cybern Sys"},{"key":"10328_CR24","doi-asserted-by":"publisher","first-page":"10597","DOI":"10.1007\/s00521-021-05793-2","volume":"33","author":"Y Zhou","year":"2021","unstructured":"Zhou Y, She Q, Ma Y (2021) Transfer of semi-supervised broad learning system in electroencephalography signal classification. Neural Comput Appl 33:10597\u201310613. https:\/\/doi.org\/10.1007\/s00521-021-05793-2","journal-title":"Neural Comput Appl"},{"issue":"3","key":"10328_CR25","doi-asserted-by":"publisher","first-page":"1037","DOI":"10.1007\/s13042-022-01680-x","volume":"14","author":"Z Wang","year":"2023","unstructured":"Wang Z, Li J, Zhang T (2023) Spectral-spatial discriminative broad graph convolution networks for hyperspectral image classification. Int J Mach Learn Cyber 14(3):1037\u20131051. https:\/\/doi.org\/10.1007\/s13042-022-01680-x","journal-title":"Int J Mach Learn Cyber"},{"issue":"2","key":"10328_CR26","first-page":"414","volume":"50","author":"F Shuang","year":"2018","unstructured":"Shuang F, Chen CLP (2018) Fuzzy broad learning system: a novel neuro-fuzzy model for regression and classification. IEEE Trans Cybern 50(2):414\u2013424","journal-title":"IEEE Trans Cybern"},{"issue":"22","key":"10328_CR27","doi-asserted-by":"publisher","first-page":"19923","DOI":"10.1007\/s00521-022-07534-5","volume":"34","author":"W Chen","year":"2022","unstructured":"Chen W, Yang K, Zhang W (2022) Double-kernelized weighted broad learning system for imbalanced data. Neural Comput Appl 34(22):19923\u201319936. https:\/\/doi.org\/10.1007\/s00521-022-07534-5","journal-title":"Neural Comput Appl"},{"issue":"8","key":"10328_CR28","doi-asserted-by":"publisher","first-page":"3017","DOI":"10.1109\/TNNLS.2019.2935033","volume":"31","author":"F Chu","year":"2020","unstructured":"Chu F, Liang T, Chen CLP, Wang X, Ma X (2020) Weighted Broad Learning System and Its Application in Nonlinear Industrial Process Modeling. IEEE Trans Neural Netw Learn Syst 31(8):3017\u20133031","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"10328_CR29","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1016\/S0165-0114(86)80034-3","volume":"20","author":"K Atanssov","year":"1986","unstructured":"Atanssov K (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20:87\u201396","journal-title":"Fuzzy Sets Syst"},{"issue":"6","key":"10328_CR30","doi-asserted-by":"publisher","first-page":"1320","DOI":"10.1109\/72.471375","volume":"6","author":"B Igelnik","year":"1995","unstructured":"Igelnik B, Pao YH (1995) Stochastic choice of basis functions inadaptive function approximation and the functional-link net. IEEE Trans Neural Netw 6(6):1320\u20131329","journal-title":"IEEE Trans Neural Netw"},{"key":"10328_CR31","unstructured":"Dheeru D, Taniskidou EK (2017) UCI machine learning repository. Available: http:\/\/archive.ics.uci.edu\/ml"},{"key":"10328_CR32","first-page":"255","volume":"17","author":"J Derrac","year":"2015","unstructured":"Derrac J, Garcia S, Sanchez L, Herrera F (2015) Keel data-mining software tool: Data set repository, integration of algorithms and experimental analysis framework. J Mult Valued Log Soft Comput 17:255\u2013287","journal-title":"J Mult Valued Log Soft Comput"},{"issue":"2","key":"10328_CR33","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1007\/s13042-011-0019-y","volume":"2","author":"GB Huang","year":"2011","unstructured":"Huang GB, Wang DH, Lan Y (2011) Extreme learning machines: a survey. Int J Mach Learn Cybern 2(2):107\u2013122","journal-title":"Int J Mach Learn Cybern"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-10328-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-024-10328-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-10328-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,28]],"date-time":"2024-09-28T16:02:42Z","timestamp":1727539362000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-024-10328-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,15]]},"references-count":33,"journal-issue":{"issue":"33","published-print":{"date-parts":[[2024,11]]}},"alternative-id":["10328"],"URL":"https:\/\/doi.org\/10.1007\/s00521-024-10328-6","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,15]]},"assertion":[{"value":"6 November 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 July 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 August 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no conflict of interest to declare that are relevant to the content of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}