Industrial development with the growth, strengthening, stability, technical advancement,
reliability, selection, and dynamic response of the power system is essential. Governments …

Deep neural networks (DNN) have remarkably progressed in applications involving large
and complex datasets but have been criticized as a black-box. This downside has recently …

Neural networks have been successfully employed in various domains such as
classification, regression and clustering, etc. Generally, the back propagation (BP) based …

Sentiment and sarcasm detection in social media contribute to assessing social opinion
trends. Over the years, most artificial intelligence (AI) methods have relied on real values to …

Abstract The use of Machine Learning (ML) has rapidly spread across several fields of
applied sciences, having encountered many applications in Structural Dynamics and …

Robotization is necessary to keep up with the constant changes in production, which calls
for a staff with robotics expertise. A manufacturing business must also have the ability to …

In recent years, adaptive network-based fuzzy inference systems (ANFIS) applied in various
engineering fields have demonstrated their ability to combine the learning capability of …

To address the issue of soft-sensing of effluent total phosphorus in wastewater treatment
processes (WWTPs), a soft-sensing system based on an adaptive recursive fuzzy neural …

As one of the three pillars in computational intelligence, fuzzy systems are a powerful
mathematical tool widely used for modelling nonlinear problems with uncertainties. Fuzzy …

In the current study, the Malathion decontamination by the aid of the UV/ferrous-activated
persulfate (PS) was investigated and the effects of pH, persulfate (PS) concentration, ferrous …