Financial data are a type of historical time series data that provide a large amount of
information that is frequently employed in data analysis tasks. The question of how to …

Human activity recognition is an emerging and important area in computer vision which
seeks to determine the activity an individual or group of individuals are performing. The …

The stock market plays a vital role in the economic and social organization of many
countries. Since stock price time series are highly noisy, nonparametric, volatility …

In this work, we present an Artificial Neural Network for operational forecasting of the SYM‐H
geomagnetic index up to 2 hr ahead using the Interplanetary Magnetic Field, the solar wind …

The stock market is a chaotic, complex, and dynamic financial market. The prediction of
future stock prices is a concern and controversial research issue for researchers. More and …

Stock price prediction is a challenging financial time-series forecasting problem. In recent
years, on account of the rapid progression of deep learning, researchers have developed …

Agricultural price forecasting, with its distinctive characteristics, remains a captivating field of
study. In countries like India, grappling with food security challenges, reliable and efficient …

Analyzing the behavior of stock market movements has often been an area of interest to
machine learning and time-series data analyst. It has been very challenging due to its …

Prediction of stock market value is highly risky because it is based on the concept of Time
Series forecasting system that can be used for investments in a safe environment with …

Applications of deep learning in financial market prediction has attracted huge attention from
investors and researchers. In particular, intra-day prediction at the minute scale, the …