Urban water supply systems are complex and dynamic in nature, and as a result, can be
considered complex to manage owing to enhanced urbanization levels, climate change …

Energy load estimation is critical for the smooth functioning of several activities, such as
reliable supply, reduced wastage, decision making and generation planning tasks. So far …

We are now living in the Intelligent Industry or Industry 4.0 era; therefore, it is very important
its application in situations that allow us to simulate and model any necessary process. In …

The use of renewable energy sources is becoming increasingly widespread around the
world due to various factors, the most relevant of which is the high environmental …

This paper develops a novel hybrid model for forecasting electrical consumption based on
several deep learning and optimization models such as Support Vector Regression (SVR) …

The goal of the research is to increase the accuracy of wind power forecasts while
maintaining the power system's stability and safety. First, the wireless sensor network (WSN) …

Time series prediction of natural calamities is effectively solved with deep neural networks
due to their ability to automatically assimilate the temporal linkages in time series data. This …

This paper aims to develop a hybrid model for forecasting electrical energy consumption of
households based on a Particle Swarm Optimization (PSO) algorithm associated with the …

Supply chain Management SCM, improving Information Sharing IS becomes increasingly
important to promote business, achieve a significant competitive advantage, and, ultimately …

Research background: In business practice and academic sphere, the question of which of
the prognostic models is the most accurate is constantly present. The accuracy of models …