Hysteresis is a natural phenomenon that widely exists in structural and mechanical systems.
The characteristics of structural hysteretic behaviors are complicated. Therefore, numerous …

In recent decades, the use of artificial intelligence (AI) techniques in the field of materials
modeling has received significant attention owing to their excellent ability to analyze a vast …

Due to efficacy and optimization potential of genetic and evolutionary algorithms, they are
used in learning and modeling especially with the advent of big data related problems. This …

Fe-based bulk metallic glasses (BMGs) are a unique class of materials that are attracting
attention in a wide variety of applications owing to their physical properties. Several studies …

Shape Memory Alloys (SMAs) are used to design actuators, which are one of the most
fascinating applications of SMA. Usually, they are on-off actuators because, in the case of …

In the present work, the endpoint sulfur content prediction model of Kambara Reactor (KR)
desulfurization in the steelmaking process is investigated. For Artificial Neural Network …

The key point of introducing quantum genetic algorithm to a quantum backpropagation
neural network model is to overcome local stagnation problem which used to be Achilles' …

Reinforced concrete structures undergo various degradation processes, mainly rebars
corrosion. Recently, magnetic non-destructive tests have been used to study the steel …

The cores of several types of electromagnetic devices (EMDs) experience a time-varying
magnetic field. Thus, the hysteresis phenomenon can be observed between flux density and …

This paper presents a soft computing of integrating artificial neural networks (ANNs) and
genetic algorithms (GAs) to back analyze the earth stress field based on hydraulic fracturing …