Gross domestic product (GDP) can effectively reflect the situation of economic development
and resource allocation in different regions. The high-precision GDP prediction technology …

Most existing recommendation systems (RSs) are primarily concerned about the accuracy of
rating prediction and only recommending popular items. However, other non-accuracy …

The prediction of time series data is very difficult. For example, the price of stocks belongs to
time series. Small fluctuations in society, politics, economy and culture may affect the stocks …

Deep reinforcement learning (DRL) has revolutionized quantitative finance by achieving
excellent performance without significant manual effort. Whereas we observe that the DRL …

In the realm of education, the timely identification of potential challenges, such as learning
difficulties leading to dropout risks, and the facilitation of personalized learning, emphasizes …

Stock prices belong to time series data, and accurate prediction of stock prices is a difficult
problem. The traditional methods of predicting stocks through statistics or regression models …

In the realm of streaming services, recommendation systems play a crucial role in meeting
user preferences by aiding them in discovering music tailored to their tastes. Reinforcement …

This study presents the design, development, and evaluation of an advanced utility
consumption monitoring and prediction platform aimed at facilitating efficient energy …

The recent rapid advancement of deep learning, especially the development of the large
language models (LLMs) has revolutionized the community of software engineering. Thanks …

These days, there are a few of application which can help the user to conducting stock
comparison and stock rating. However, these applications cannot directly predict the stock …