Background As the application of Artificial Intelligence (AI) technologies increases in the
healthcare sector, the industry faces a need to combine medical knowledge, often …

Modal-decomposition techniques are computational frameworks based on data aimed at
identifying a low-dimensional space for capturing dominant flow features: the so-called …

In this article, we extend the popular supervised learning technique radial basis function
network (RBFN) for regression modeling based on fuzzy responses and exact predictors …

When dealing with nonparametric regression problems, kernel-based methods are often
employed. In this paper, we investigate nonparametric regression problems with fuzzy …

The purpose of this study is to develop a new fuzzy regression model based on a common
Bayesian nonparametric-based method with exact predictors and fuzzy responses. To this …

Mission-oriented UAV networks operate in nonsecure, complex environments with time-
varying network partitioning and node trustworthiness. UAV networks are thus essentially …

It is crucial for valid statistical inference to make appropriate assumptions about the data
generating process, which is why specific assumptions have to be formulated very carefully …

In data analysis, analyzing the relationships between the variables such as correlation
analysis and regression analysis are very important. Correlation analysis and regression …

Quantile regression estimates conditional quantiles and has found extensive applications in
real-life statistical procedures. This study assessed a new for nonlinear quantile regression …

The role of the regression analysis is crucial in many disciplines. Addressing the fuzzy
quadratic least square regression for observed data modeled by fuzzy numbers, we aim to …