𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Insight of a fuzzy regression model

✍ Scribed by Hsiao-Fan Wang; Ruey-Chyn Tsaur

Publisher
Elsevier Science
Year
2000
Tongue
English
Weight
202 KB
Volume
112
Category
Article
ISSN
0165-0114

No coin nor oath required. For personal study only.

✦ Synopsis

Fuzzy regression, a nonparametric method, can be quite useful in estimating the relationships among variables where the available data are very limited and imprecise, and variables are interacting in an uncertain, qualitative, and fuzzy way. Thus, it may have considerably practical applications in many management and engineering problems. But there is still lack of proper interpretation about fuzzy regression. In this paper, we provide an insight into regression intervals so that regression interval analysis, data type analysis and variable selections can be analytically performed. Numerical examples are provided for illustration.

πŸ“œ SIMILAR VOLUMES

Improved fuzzy partitions for fuzzy regr
Improved fuzzy partitions for fuzzy regression models
✍ Frank HΓΆppner; Frank Klawonn πŸ“‚ Article πŸ“… 2003 πŸ› Elsevier Science 🌐 English βš– 641 KB

Fuzzy clustering algorithms like the popular fuzzy c-means algorithm (FCM) are frequently used to automatically divide up the data space into fuzzy granules. When the fuzzy clusters are used to derive membership functions for a fuzzy rule-based system, then the corresponding fuzzy sets should fulfil

Evaluation of fuzzy regression models by
Evaluation of fuzzy regression models by fuzzy neural network
✍ M. Mosleh; M. Otadi; S. Abbasbandy πŸ“‚ Article πŸ“… 2010 πŸ› Elsevier Science 🌐 English βš– 378 KB

## a b s t r a c t In this paper, a novel hybrid method based on fuzzy neural network for approximate fuzzy coefficients (parameters) of fuzzy linear and nonlinear regression models with fuzzy output and crisp inputs, is presented. Here a neural network is considered as a part of a large field call