The technological advancements and environmental concerns enlighten the importance of
incorporating more high-performance engineered materials in the construction sector. The …

One of the challenges in the successful implementation of deep neural network (DNN) is
setting the value for various hyper-parameters, one of which is the network topology, which …

Wetlands are one of the world's most significant and vulnerable ecosystems. The wetlands
of the Yellow River Delta are subject to multiple influences of ocean tidal action and the …

Facial expression is one of the most effective and universal ways to express emotions and
intentions. It reflects what a person is thinking or experiencing. Thus, the expression …

The electric power grid is a complex, interconnected cyber-physical system comprised of
collaborating elements for monitoring and control. Distributed controllers play a prominent …

Class imbalance is a critical challenge in big data analytics, often leading to biased
predictive models. This imbalance can lead to biased models that perform well on the …

This study explores the development and evaluation of a neural network model for
predicting diabetes based on clinical data. The model was built using the Keras API with …

Identification of optimal number of neurons and layers in a proposed neural architecture is
very complex for the better results. The determination of the hidden layer number is also very …

In this dissertation, we propose a novel day-ahead load forecasting method that can be
applied without manual setup on any building and is more accurate than currently existing …

An approach to predicting the viscosity and density of petroleum products using artificial
neural networks was proposed. Based on reliable data on the thermophysical properties …