Atmospheric extreme events cause severe damage to human societies and ecosystems.
The frequency and intensity of extremes and other associated events are continuously …

Atmospheric Extreme Events (EEs) cause severe damages to human societies and
ecosystems. The frequency and intensity of EEs and other associated events are increasing …

The consistently growing demand for airline transportation has resulted in increased air
traffic and air operations in airports across the world. According to the International Air …

Currently, the use of deep learning for solving ordinal classification problems, where
categories follow a natural order, has not received much attention. In this paper, we propose …

Deep learning techniques for ordinal classification have recently gained significant attention.
Predicting an ordinal variable, that is, a variable that demonstrates a natural relationship …

The purpose of this paper is to introduce a new distance metric learning algorithm for ordinal
regression. Ordinal regression addresses the problem of predicting classes for which there …

Dropout is a popular regularisation tool for deep neural classifiers, but it is applied
regardless of the nature of the classification task: nominal or ordinal. Consequently, the …

This paper presents a method for providing explainability in the integration of artificial
intelligence (AI) and data mining techniques when dealing with meteorological prediction …

In this paper we present a novel methodology, referenced as ORFEO (Ordinal classifier and
Regressor Fusion for Estimating an Ordinal categorical target), to enhance the performance …

In the hot rolling industry, a high-precision quality determination framework is the guarantee
for intelligent decision-making regarding products. Conventional methods ignore the …