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Majority of the methods are application domain dependent and complex. In this paper, a simple method for the construction of membership functions from numerical data is proposed. To validate the proposed method, commonly used and suggested evaluation measures: average error rate, mean magnitude of relative error (MMRE), balanced mean magnitude of relative error (BMMRE), and coefficient of determination (R\n                    <jats:sup>2<\/jats:sup>\n                    ), have been taken. The validating results show that proposed method has a higher accuracy than existing methods. The sensitivity analysis has been performed to analyze the impact of input variable on the output variable.\n                  <\/jats:p>","DOI":"10.3233\/ifs-151698","type":"journal-article","created":{"date-parts":[[2015,11,10]],"date-time":"2015-11-10T11:36:43Z","timestamp":1447155403000},"page":"2227-2233","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":6,"title":["A method for generating membership function from numerical data"],"prefix":"10.1177","volume":"29","author":[{"given":"Harikesh Bahadur","family":"Yadav","sequence":"first","affiliation":[{"name":"Department of Computer Applications, National Institute of Technology, Jamshedpur, Jahrkhand, India"}]},{"given":"Dilip Kumar","family":"Yadav","sequence":"additional","affiliation":[{"name":"Department of Computer Applications, National Institute of Technology, Jamshedpur, Jahrkhand, 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