{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,2]],"date-time":"2025-10-02T06:10:57Z","timestamp":1759385457997,"version":"3.40.5"},"reference-count":21,"publisher":"Wiley","license":[{"start":{"date-parts":[[2020,12,18]],"date-time":"2020-12-18T00:00:00Z","timestamp":1608249600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Scientific Programming"],"published-print":{"date-parts":[[2020,12,18]]},"abstract":"<jats:p>With respect to the cluster problem of the evaluation information of mass customers in service management, a cluster algorithm of new Gaussian kernel FCM (fuzzy C-means) is proposed based on the idea of FCM. First, the paper defines a Euclidean distance formula between two data points and makes them cluster adaptively based on the distance classification approach and nearest neighbors in deleting relative data. Second, the defects of the FCM algorithm are analyzed, and a solution algorithm is designed based on the dual goals of obtaining a short distance between whole classes and long distances between different classes. Finally, an example is given to illustrate the results compared with the existing FCM algorithm.<\/jats:p>","DOI":"10.1155\/2020\/8889480","type":"journal-article","created":{"date-parts":[[2020,12,19]],"date-time":"2020-12-19T17:35:05Z","timestamp":1608399305000},"page":"1-6","source":"Crossref","is-referenced-by-count":7,"title":["Gaussian Kernel Fuzzy C-Means Algorithm for Service Resource Allocation"],"prefix":"10.1155","volume":"2020","author":[{"given":"Wei","family":"Jiang","sequence":"first","affiliation":[{"name":"College of Economics and Management, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710061, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1680-3057","authenticated-orcid":true,"given":"Xi","family":"Fang","sequence":"additional","affiliation":[{"name":"School of Economics and Management, Shanghai Institute of Technology, Shanghai 200235, China"}]},{"given":"Jianmei","family":"Ding","sequence":"additional","affiliation":[{"name":"School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China"}]}],"member":"311","reference":[{"issue":"3","key":"1","first-page":"30","article-title":"Improvement of semi-supervised kernel clustering algorithm based on multi-factor stock selection","volume":"33","author":"W. Li","year":"2018","journal-title":"Statistics and Information Forum"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2015.05.079"},{"key":"3","article-title":"Hesitant fuzzy language condensed hierarchical clustering algorithm and its application","volume":"21","author":"Z. Zhang","year":"2019","journal-title":"Statistics and Decision"},{"key":"4","doi-asserted-by":"crossref","DOI":"10.1016\/j.trb.2016.04.011","article-title":"Modeling of yard congestion and optimization of yard template in container ports","volume":"90","author":"L. Zhen","year":"2016","journal-title":"Transportation Research Part B Methodological"},{"key":"5","first-page":"3220","article-title":"A FCM clustering algorithm based on polygonal fuzzy numbers to describe multiple attribute index information","volume":"12","author":"Y. Duan","year":"2016","journal-title":"Systems Engineering-Theory and Practice"},{"issue":"3","key":"6","first-page":"47","article-title":"A novel clustering algorithm based on graph theory","volume":"45","author":"D. Ying","year":"2009","journal-title":"Computer Engineering and Application"},{"key":"7","first-page":"29","article-title":"On gray prediction model based on an improved FCM algorithm","volume":"09","author":"Y. Xue","year":"2017","journal-title":"Statistics and Decision"},{"issue":"6","key":"8","first-page":"206","article-title":"Improved fuzzy C-means clustering algorithm based on selecting initial clustering center","volume":"36","author":"H. Zhang","year":"2009","journal-title":"Computer Science"},{"first-page":"1240","article-title":"A cluster estimation method with extension to fuzzy model identification","author":"L. Chiu Stephen","key":"9"},{"key":"10","doi-asserted-by":"crossref","first-page":"9695","DOI":"10.1016\/j.eswa.2012.02.149","article-title":"A new grouping genetic algorithm for clustering problems","volume":"39","author":"L. E. Agustin-Blas","year":"2012","journal-title":"Expert Systems with Application"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2009.06.009"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2010.09.040"},{"issue":"6","key":"13","first-page":"75","article-title":"Extended incremental fuzzy clustering algorithm for sparse high-dimensional big data","volume":"45","author":"X. Qian","year":"2019","journal-title":"Computer Engineering"},{"issue":"1","key":"14","first-page":"134","article-title":"Research on fast parallel clustering algorithm for large scale data","volume":"39","author":"X. Niu","year":"2012","journal-title":"Computer Science"},{"issue":"2","key":"15","first-page":"157","article-title":"Improved hierarchical K-means clustering algorithm","volume":"49","author":"W. Hu","year":"2013","journal-title":"Computer Engineering and Applications"},{"issue":"9","key":"16","first-page":"2664","article-title":"Single pass bayesian fuzzy clustering","volume":"29","author":"J. Liu","year":"2018","journal-title":"Journal of Software"},{"issue":"11","key":"17","first-page":"2314","article-title":"Data-weighted fuzzy C-means clustering algorithm","volume":"36","author":"S. Zhou","year":"2014","journal-title":"Systems Engineering and Electronics"},{"issue":"11","key":"18","first-page":"1695","article-title":"Improved clustering algorithm and its application in complex huge group decision-making","volume":"28","author":"X. Chen","year":"2006","journal-title":"Systems Engineering and Electronics"},{"key":"19","doi-asserted-by":"publisher","DOI":"10.1080\/01431161.2018.1541366"},{"issue":"1","key":"20","first-page":"219","article-title":"Research on adaptive entropy weight fuzzy C-means clustering algorithm","volume":"36","author":"H. Huang","year":"2016","journal-title":"Systems Engineering-Theory & Practice"},{"issue":"2","key":"21","first-page":"346","article-title":"Improved ants-clustering algorithm and its application in multi-attribute large group decision making","volume":"33","author":"X. Xu","year":"2011","journal-title":"Systems Engineering and Electronics"}],"container-title":["Scientific Programming"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/sp\/2020\/8889480.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/sp\/2020\/8889480.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/sp\/2020\/8889480.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,12,19]],"date-time":"2020-12-19T17:35:40Z","timestamp":1608399340000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/sp\/2020\/8889480\/"}},"subtitle":[],"editor":[{"given":"Xiaobo","family":"Qu","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2020,12,18]]},"references-count":21,"alternative-id":["8889480","8889480"],"URL":"https:\/\/doi.org\/10.1155\/2020\/8889480","relation":{},"ISSN":["1875-919X","1058-9244"],"issn-type":[{"type":"electronic","value":"1875-919X"},{"type":"print","value":"1058-9244"}],"subject":[],"published":{"date-parts":[[2020,12,18]]}}}