A bilevel programming model represents the relationship in a specific decision process that
involves decisions within a hierarchical structure of two levels. The upper-level problem is …

The main goal of machine learning is the creation of self-learning algorithms in many areas
of human activity. It allows a replacement of a person with artificial intelligence in seeking to …

Abstract Deep Neural Networks (DNNs) are widely regarded as the most effective learning
tool for dealing with large datasets, and they have been successfully used in thousands of …

At present times, COVID-19 has become a global illness and infected people has increased
exponentially and it is difficult to control due to the non-availability of large quantity of testing …

We consider a deep learning model for classifying high-dimensional data and seek to
achieve optimal evaluation accuracy and robustness based on multicriteria decision-making …

Convolutional neural networks (CNNs) are a superb computing paradigm in deep learning,
and their architectures are considered to be the key to performance breakthroughs in …

Abstract Knowledge extraction through machine learning techniques has been successfully
applied in a large number of application domains. However, apart from the required …

In this paper, individual and hybrid methods are proposed employing optimized statistical
and deep learning (DL) models for deterministic (point) and probabilistic (interval) …

Artificial Neural Networks (ANNs) are machine learning algorithms inspired by the structure
and function of the human brain. Their popularity has increased in recent years due to their …

Real estate is potentially contributing to the economic growth. It has a strong correlation
between property owners and beneficiaries. The accurate forecast of future property prices …