Two Robust Fuzzy Regression Models and Their Applications in Predicting Imperfections of Cotton Yarn
Author(s):
Abstract:
Using the generalized Hausdorff-metric, two least-absolutes (LA) approaches to multiple fuzzy regression modeling are introduced for the case of crisp input-fuzzy output data. The main advantage of the proposed models is that they are not so sensitive to the outlier data points. The proposed models as well as two common fuzzy least-squares (LS) models are employed in a case study to estimate imperfections of cotton yarn using fiber properties in a reallife data. In order to derive the fuzzy regression models between imperfections of cotton yarn and fiber properties, first, effective variables are selected by the statistical stepwise test. Then, four fuzzy models, including two new LA models and two LS models, are sought to fit the data set.
Finally, two criteria are employed to evaluate the goodness-of-fit of models. Moreover, a predictive ability index is introduced and employed to evaluate the predictability of the models. Using these criteria, a comparative study between the proposed fuzzy least-absolutes regression models and fuzzy least-squares regression models has also been addressed. The comparison results reveal that the LA-fuzzy models perform better than the LS-fuzzy models in imperfections of cotton yarn estimation for the particular data set used in this study.
Finally, two criteria are employed to evaluate the goodness-of-fit of models. Moreover, a predictive ability index is introduced and employed to evaluate the predictability of the models. Using these criteria, a comparative study between the proposed fuzzy least-absolutes regression models and fuzzy least-squares regression models has also been addressed. The comparison results reveal that the LA-fuzzy models perform better than the LS-fuzzy models in imperfections of cotton yarn estimation for the particular data set used in this study.
Keywords:
Language:
English
Published:
Journal of Textiles and Polymers, Volume:4 Issue: 2, Spring 2016
Pages:
60 to 68
magiran.com/p1685233
دانلود و مطالعه متن این مقاله با یکی از روشهای زیر امکان پذیر است:
اشتراک شخصی
با عضویت و پرداخت آنلاین حق اشتراک یکساله به مبلغ 1,390,000ريال میتوانید 70 عنوان مطلب دانلود کنید!
اشتراک سازمانی
به کتابخانه دانشگاه یا محل کار خود پیشنهاد کنید تا اشتراک سازمانی این پایگاه را برای دسترسی نامحدود همه کاربران به متن مطالب تهیه نمایند!
توجه!
- حق عضویت دریافتی صرف حمایت از نشریات عضو و نگهداری، تکمیل و توسعه مگیران میشود.
- پرداخت حق اشتراک و دانلود مقالات اجازه بازنشر آن در سایر رسانههای چاپی و دیجیتال را به کاربر نمیدهد.
In order to view content subscription is required
Personal subscription
Subscribe magiran.com for 70 € euros via PayPal and download 70 articles during a year.
Organization subscription
Please contact us to subscribe your university or library for unlimited access!