fuzzy linear regression based on least absolutes deviations

نویسندگان

s. m. taheri

m. kelkinnama

چکیده

this study is an investigation of fuzzy linear regression model for crisp/fuzzy input and fuzzy output data. a least absolutes deviations approach to construct such a model is developed by introducing and applying a new metric on the space of fuzzy numbers. the proposed approach, which can deal with both symmetric and non-symmetric fuzzy observations, is compared with several existing models by three goodness of t criteria. three well-known data sets including two small data sets as well as a large data set are employed for such comparisons.

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عنوان ژورنال:
iranian journal of fuzzy systems

ناشر: university of sistan and baluchestan

ISSN 1735-0654

دوره 9

شماره 1 2012

میزبانی شده توسط پلتفرم ابری doprax.com

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