Abstract: The retail sales sector plays a significant role in the global economy, contributing over 15% of global GDP. The rapid growth of e-commerce has made business forecasting increasingly crucial ...

├── src/ # Source code modules │ ├── lstm_model.py # LSTM implementation with PyTorch │ ├── forecasting_models.py # ARIMA, Prophet, and statistical models │ ├── anomaly_detection.py # Anomaly ...

ABSTRACT: Accurate forecasting of the system marginal price (SMP) is crucial to improve demand-side management and optimize power generation scheduling. However, predicting the SMP is challenging due ...

Researchers have developed a hybrid AI model that significantly improves the accuracy and environmental sustainability of solar power forecasting. The study advances practical tools to support the ...

The application of virtual reality (VR) in industrial training and safety emergency needs to reflect realistic changes in physical object properties. However, existing VR systems still lack fast and ...

This study proposes a hybrid modeling approach that integrates a Physics Informed Neural Network (PINN) and a long short-term memory (LSTM) network to predict river water temperature in a defined ...

Nurul is a passionate writer and an avid gamer from Malaysia. Once she is attracted to a certain game, she unknowingly speedruns at the maximum pace to complete it and creates straightforward guides ...

A reward shaping deep deterministic policy gradient (RS-DDPG) and simultaneous localization and mapping (SLAM) path tracking algorithm is proposed to address the issues of low accuracy and poor ...

Abstract: Deep reinforcement learning has shown great potential in the field of robot control, but it still faces challenges in continuous control tasks. Traditional reinforcement learning algorithms ...