This research initiative highlights the importance of ethical and explainable artificial intelligence in workforce ...

This paper explores effective methods for predicting gold prices, proposing three modeling strategies: a standalone Long Short-Term Memory (LSTM) network, a Convolutional Self-Attention (CSA) Network, ...

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In the context of global energy shortages, traditional energy sources face issues of limited reserves and high prices. As a result, the importance of energy storage technology is increasingly ...

This research presents a hybrid CNN-LSTM model for predicting cotton production using remote sensing data. The model integrates the spatial feature extraction capability of Convolutional Neural ...

With the widespread application of lithium-ion batteries in electric vehicles and energy storage systems, health monitoring and remaining useful life prediction have become critical components of ...

This paper explores the integration of Artificial Intelligence (AI) large language models to empower the Python programming course for junior undergraduate students in the electronic information ...

Landslides are one of the most prevalent natural geological disasters, causing significant economic losses, damaging public environments, and posing severe threats to human lives. Landslide ...

Abstract: In this paper, the LSTM model is used to predict the stock prices of the top 10 constituents of CSI 300 index and construct a portfolio. The empirical results show that the LSTM model ...