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A number of algorithms have been developed for the normal parameter reduction of soft set but the case of repeated columns (i.e.,\n                    <jats:italic>e<\/jats:italic>\n                    <jats:sub>\n                      <jats:italic>i<\/jats:italic>\n                    <\/jats:sub>\n                    \u00a0=\u00a0\n                    <jats:italic>e<\/jats:italic>\n                    <jats:sub>\n                      <jats:italic>j<\/jats:italic>\n                    <\/jats:sub>\n                    ) was only considered by Danjuma et al. In this study, first we address the limitations of the Danjuma et al.\u2019s approach to normal parameter reduction of soft set. Then, we propose a new algorithm for normal parameter reduction of soft set which is free of all such limitations. Moreover, we compare the proposed algorithm with some of the existing algorithms of normal parameter reduction of soft set to show its efficiency. Finally, the application of the proposed algorithm is elaborated by a medical diagnostic problem.\n                  <\/jats:p>","DOI":"10.3233\/jifs-190071","type":"journal-article","created":{"date-parts":[[2019,6,25]],"date-time":"2019-06-25T12:50:09Z","timestamp":1561467009000},"page":"2953-2968","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":10,"title":["An improved algorithm for normal parameter reduction of soft set"],"prefix":"10.1177","volume":"37","author":[{"given":"Abid","family":"Khan","sequence":"first","affiliation":[{"name":"School of Science, Nanjing University of Science and Technology, Nanjing, China"}]},{"given":"Yuanguo","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Science, Nanjing University of Science and Technology, Nanjing, 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