Time series forecasting has become a very intensive field of research, which is even
increasing in recent years. Deep neural networks have proved to be powerful and are …

In recent years, deep learning techniques have outperformed traditional models in many
machine learning tasks. Deep neural networks have successfully been applied to address …

Energy efficiency of public sector is an important issue in the context of smart cities due to
the fact that buildings are the largest energy consumers, especially public buildings such as …

Early and timely detection of surface damages is important for maintaining the functionality,
reliability, and safety of concrete bridges. Recent advancement in convolution neural …

Nowadays, electricity is a basic commodity necessary for the well-being of any modern
society. Due to the growth in electricity consumption in recent years, mainly in large cities …

This research proposes and evaluates a new approach for flash flood susceptibility map**
based on Deep Learning Neural Network (DLNN)) algorithm, with a case study at a high …

Autism spectrum disorder (ASD) is a neurodevelopmental incurable disorder with a long
diagnostic period encountered in the early years of life. If diagnosed early, the negative …

Abstract In the Big Data Era, recommender systems perform a fundamental role in data
management and information filtering. In this context, Collaborative Filtering (CF) persists as …

The economic sector is one of the most important pillars of countries. Economic activities of
industry are intimately linked with the ability to meet their needs for electricity. Therefore …

The current bridge maintenance practice generally involves manual visual inspection, which
is highly subjective and unreliable. A technique that can automatically detect defects, for …