{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,15]],"date-time":"2026-02-15T12:06:14Z","timestamp":1771157174798,"version":"3.50.1"},"reference-count":0,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2009,5,1]],"date-time":"2009-05-01T00:00:00Z","timestamp":1241136000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2009,5]]},"abstract":"<jats:p>This paper presents a multi-class Support Vector Machine (SVM) based\n\t\t\t algorithm for on-line static security assessment of the power systems. The\n\t\t\t proposed SVM based security assessment algorithm has a very small training time\n\t\t\t and space in comparison with the traditional machine learning methods such as\n\t\t\t Artificial Neural Networks (ANN) based algorithms. In addition, the proposed\n\t\t\t algorithm is faster than existing algorithms. One of the main points, to apply\n\t\t\t a machine learning method is feature selection. In this paper, a new Decision\n\t\t\t Tree (DT) based feature selection algorithm has been presented. The proposed\n\t\t\t SVM algorithm has been applied to New England 39-bus power system. The\n\t\t\t simulation results show the effectiveness and the stability of the proposed\n\t\t\t method for on-line static security assessment. The effectiveness of the\n\t\t\t proposed feature selection algorithm has been investigated, too. The proposed\n\t\t\t feature selection algorithm has been compared with different feature selection\n\t\t\t algorithms. The simulation results demonstrate the effectiveness of the\n\t\t\t proposed feature algorithm.<\/jats:p>","DOI":"10.3233\/ifs-2009-0421","type":"journal-article","created":{"date-parts":[[2019,12,2]],"date-time":"2019-12-02T17:40:07Z","timestamp":1575308407000},"page":"133-146","source":"Crossref","is-referenced-by-count":5,"title":["Application of multi-class support vector machines for power\t\t\t system on-line static security assessment using DT - based feature and data\t\t\t selection algorithms"],"prefix":"10.1177","volume":"20","author":[{"given":"M.","family":"Mohammadi","sequence":"first","affiliation":[{"name":"No. 424, Hafez Ave, Electrical Engineering Department,\r\t\t\t Amirkabir University of Technology, 15914, Tehran, Iran"}]},{"given":"G.B.","family":"Gharehpetian","sequence":"additional","affiliation":[{"name":"No. 424, Hafez Ave, Electrical Engineering Department,\r\t\t\t Amirkabir University of Technology, 15914, Tehran, Iran"}]}],"member":"179","published-online":{"date-parts":[[2009,5]]},"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/IFS-2009-0421","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/IFS-2009-0421","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,15]],"date-time":"2026-02-15T11:47:48Z","timestamp":1771156068000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.3233\/IFS-2009-0421"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009,5]]},"references-count":0,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2009,5]]}},"alternative-id":["10.3233\/IFS-2009-0421"],"URL":"https:\/\/doi.org\/10.3233\/ifs-2009-0421","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2009,5]]}}}