APPROACH TO CHOOSING THE FUZZY REGRESSION MODEL IN THE PROBLEM OF ANALYZING THE INDICATORS OF SOCIO-ECONOMIC SPHERE, REPRESENTED BY THE TIME SERIES

2020 ◽  
Vol 71 ◽  
pp. 83-96
Author(s):  
L. A. Demidova ◽  
◽  
M. A. Stepanov ◽  
Keyword(s):  
Time Series ◽  
Regression Model ◽  
Fuzzy Regression ◽  
Fuzzy Regression Model ◽  
Economic Sphere

The Aspects of Choosing the Time Series Length when Constructing a Fuzzy Regression Model

2021 ◽  
Author(s):  
Liliya Anatolievna Demidova ◽  
Maksim Anatolievich Stepanov
Keyword(s):  
Time Series ◽  
Regression Model ◽  
Fuzzy Regression ◽  
Series Length ◽  
Fuzzy Regression Model

A new hybrid artificial neural networks and fuzzy regression model for time series forecasting

2008 ◽  
Vol 159 (7) ◽  
pp. 769-786 ◽  
Author(s):  
Mehdi Khashei ◽  
Seyed Reza Hejazi ◽  
Mehdi Bijari
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Artificial Neural Networks ◽  
Regression Model ◽  
Time Series Forecasting ◽  
Fuzzy Regression ◽  
Fuzzy Regression Model ◽  
Artificial Neural

FUZZY REGRESSION MODEL OF METALLURGICAL PRODUCTS INDUSTRY SUPPLIES PLANNING

2019 ◽  
Vol 3 (90) ◽  
pp. 9-16
Author(s):  
Daria Gorchakova ◽  
Victor Shabalov
Keyword(s):  
Regression Model ◽  
Fuzzy Regression ◽  
Fuzzy Regression Model

An Analysis of Poverty in Italy through a Fuzzy Regression Model

2011 ◽  
pp. 342-355 ◽  
Author(s):  
Silvestro Montrone ◽  
Francesco Campobasso ◽  
Paola Perchinunno ◽  
Annarita Fanizzi
Keyword(s):  
Regression Model ◽  
Fuzzy Regression ◽  
Fuzzy Regression Model

scholarly journals Quadrilateral Interval Type-2 Fuzzy Regression Analysis for Data Outlier Detection

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Pingping Gao ◽  
Yabin Gao
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Outlier Detection ◽  
Euclidean Distance ◽  
Fuzzy Numbers ◽  
Fuzzy Regression ◽  
Fuzzy Regression Analysis ◽  
Fuzzy Regression Model ◽  
Interval Type

This paper presents a fuzzy regression analysis method based on a general quadrilateral interval type-2 fuzzy numbers, regarding the data outlier detection. The Euclidean distance for the general quadrilateral interval type-2 fuzzy numbers is provided. In the sense of Euclidean distance, some parameter estimation laws of the type-2 fuzzy linear regression model are designed. Then, the data outlier detection-oriented parameter estimation method is proposed using the data deletion-based type-2 fuzzy regression model. Moreover, based on the fuzzy regression model, by using the root mean squared error method, an impact evaluation rule is designed for detecting data outlier. An example is finally provided to validate the presented methods.

Fuzzy regression model clustering algorithm based assessment, analysis and acceptance of palliative care and psychological behaviors of elderly patients with cancer pain

2018 ◽  
Vol 22 (S2) ◽  
pp. 4813-4820
Author(s):  
Ke Xi ◽  
Luo Huiyu ◽  
He Xiaohua ◽  
Wu Meihua ◽  
Wu Guangfeng ◽  
...  
Keyword(s):  
Palliative Care ◽  
Elderly Patients ◽  
Cancer Pain ◽  
Regression Model ◽  
Clustering Algorithm ◽  
Fuzzy Regression ◽  
Patients With Cancer ◽  
Fuzzy Regression Model

Nephropathy forecasting in diabetic patients using a GA-based type-2 fuzzy regression model

2017 ◽  
Vol 37 (2) ◽  
pp. 281-289 ◽  
Author(s):  
Narges Shafaei Bajestani ◽  
Ali Vahidian Kamyad ◽  
Ensieh Nasli Esfahani ◽  
Assef Zare
Keyword(s):  
Regression Model ◽  
Fuzzy Regression ◽  
Diabetic Patients ◽  
Fuzzy Regression Model
Sign in / Sign up

Export Citation Format

Share Document