Stock market is one of the attractive domains for researchers as well as academicians. It
represents highly complex non-linear fluctuating market behaviours where traders …

As a significant issue in the machine learning field, the long-term forecasting of time series
has aroused extensive attention from academia and industry. Specifically, transforming time …

Capturing time and frequency relationships of time series signals offers an inherent barrier
for automatic human activity recognition (HAR) from wearable sensor data. Extracting …

Machine Learning and Deep Learning-based stock market prediction models are in trend.
Various methods and algorithms are there to deal with stock market analysis. However, an …

Abstract Information fusion is one of the critical aspects in diverse fields of applications;
while the collected data may provide certain perspectives, a fusion of such data can be a …

Financial accounting information systems (FAISs) are one of the scientific fields where deep
learning (DL) and swarm-based algorithms have recently seen increased use. Nevertheless …

As the economy has grown rapidly in recent years, more and more people have begun
putting their money into the stock market. Thus, predicting trends in the stock market is …

This paper determines the most affected stock market by COVID-19 among GCC stock
markets and extracts the factors that increase this effect. Recommendations from the …

Multilayer piezocomposite transducers are widely used in many applications where broad
bandwidth is required for tracking and detection purposes. However, it is difficult to operate …

The fish processing sector is experiencing increased pressure to reduce its energy
consumption and carbon footprint as a response to (a) an increasingly stringent energy …