Abstract Machine learning models have made significant progress in load forecasting, but
their forecast accuracy is limited in cases where historical load data is scarce. Inspired by …

Cryptocurrencies, most notably Bitcoin, have experienced a significant increase in
popularity, garnering the interest of both investors and scholars. The present study aims to …

Aquatic organisms serve as crucial indicators of ecosystem health and water quality
conditions. Accurate classification and monitoring of aquatic organisms facilitate the timely …

Accurately predicting market direction is crucial for informed trading decisions to buy or sell
stocks. This study proposes a deep learning based hybrid approach combining …

Speech emotion recognition is an area of research dedicated to identifying and categorizing
emotions expressed through speech. Its purpose is to comprehend and interpret the …

An addition of soft set theory, Neutrosophic soft set theory offers a versatile framework for
handling indeterminacy and uncertainty in data. Using this theory for the prediction of market …

Parkinson's disease (PD) arises from the degeneration of neurons and the subsequent
depletion of dopamine, resulting in symptoms such as tremors, muscle rigidity, and …

Education on cryptocurrency is essential for individuals to make informed decisions
regarding foreign investment in digital assets. In recent years there is an exponential …

In the realm of autonomous vehicles, learning is achieved through reinforcement learning.
To illustrate, let's consider the task of training a self-driving car to apply the brakes when it …

This research investigates the viability of Long Short-Term Memory (LSTM) systems, a
subtype of Recurrent Neural Networks (RNNs), for picture captioning. Leveraging the MS …