Stock market forecasting has been a subject of interest for many researchers; the essential
market analyses can be integrated with historical stock market data to derive a set of …

Not only market signals but also disturbances of related companies influence the stock
volatility of a company. Currently, most approaches that utilize inter-stock correlations rely on …

Abstract Autonomous Guided Vehicles (AGVs) are nowadays an indispensable component
of production lines in smart manufacturing. Managing the fleet of AGVs covers not only the …

Many studies have employed reinforcement learning (RL) techniques to successfully create
portfolio strategies in recent years. However, since financial markets are extremely noisy …

Intelligent forecasting model of stock price is an effective way to obtain ideal investment
returns. Due to the impact of quantitative transactions, traditional forecasting methods face …

Stability and security issues in energy management have become widespread research
topics, in which artificial intelligence techniques are often embedded in management …

Pattern mining (PM) is an important field of data mining and has gained considerable
momentum recently, mainly owing to the massive growth of big data. PM often sets attentive …

Renewable energy generation has attracted the interest of researchers, but it is volatile, and
management systems are vulnerable to malicious attacks. Therefore, security issues are of …

Abstract Deep Reinforcement Learning (DRL) algorithms have been increasingly used to
construct stock trading strategies, but they often face performance challenges when applied …

With the emergence of artificial intelligence, deep learning techniques have been widely
deployed in forecasting stock markets. However, existing deep-learning-based models for …