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Neutrosophic clustering is the generalization of fuzzy clustering and has been applied to many fields. This paper presents a new neutrosophic clustering algorithm with the help of regularization. Firstly, the regularization term is introduced into the FC\u2010PFS algorithm to generate sparsity, which can reduce the complexity of the algorithm on large data sets. Secondly, we propose a method to simplify the process of determining regularization parameters. Finally, experiments show that the clustering results of this algorithm on artificial data sets and real data sets are mostly better than other clustering algorithms. Our clustering algorithm is effective in most cases.<\/jats:p>","DOI":"10.1155\/2021\/6657849","type":"journal-article","created":{"date-parts":[[2021,1,30]],"date-time":"2021-01-30T19:35:05Z","timestamp":1612035305000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Neutrosophic Clustering Algorithm Based on Sparse Regular Term Constraint"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7870-6770","authenticated-orcid":false,"given":"Dan","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3356-7535","authenticated-orcid":false,"given":"Yingcang","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3094-1210","authenticated-orcid":false,"given":"Hu","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8447-6430","authenticated-orcid":false,"given":"Xiaofei","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,1,30]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2020.2989098"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.05.102"},{"key":"e_1_2_9_3_2","first-page":"157","article-title":"Algorithms for fuzzy clustering","volume":"229","author":"Miyamto S.","year":"2008","journal-title":"Studies in Fuzziness and Soft Computing"},{"key":"e_1_2_9_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/s0019-9958(65)90241-x"},{"key":"e_1_2_9_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.06.050"},{"key":"e_1_2_9_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.06.009"},{"key":"e_1_2_9_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.06.006"},{"key":"e_1_2_9_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2011.2170702"},{"key":"e_1_2_9_9_2","doi-asserted-by":"publisher","DOI":"10.1002\/9780470061190"},{"key":"e_1_2_9_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/0098-3004(84)90020-7"},{"key":"e_1_2_9_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/tfuzz.2006.889763"},{"key":"e_1_2_9_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/tfuzz.2012.2187453"},{"key":"e_1_2_9_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/s0165-0114(86)80034-3"},{"key":"e_1_2_9_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2010.05.005"},{"key":"e_1_2_9_15_2","doi-asserted-by":"publisher","DOI":"10.1504\/ijbidm.2008.017975"},{"key":"e_1_2_9_16_2","doi-asserted-by":"publisher","DOI":"10.1142\/s0219622013500053"},{"key":"e_1_2_9_17_2","first-page":"409","article-title":"Picture fuzzy sets","volume":"30","author":"Cuong B. 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