The scope of application of generative artificial intelligence (GAI) in industrial functions is
gaining high prominence in academic and industrial discourses. In this article, we explore …

Prediction results in big data analysis can vary greatly depending on the data preprocessing
methods used. Time series-based processing methods are particularly advantageous for …

Pragmatics, situated in the domains of linguistics and computational linguistics, explores the
influence of context on language interpretation, extending beyond the literal meaning of …

Existing surveys on stock market prediction often focus on traditional machine learning
methods instead of deep learning methods. This motivates us to provide a structured and …

Until recently, the supply chain sector, which had been getting by with scattered
spreadsheets, phone conversations, and even paper-based records until recently, was …

To improve the accuracy of soybean futures price prediction, this paper constructs a
sentiment index considering investor concern (ICSI) based on news text, Baidu search …

The intermittence and fluctuation of renewable energy bring significant uncertainty to the
power system, which enormously increases the operational risks of the power system. The …

This study designs a new TODIM-based multi-attribute decision making (MADM) method
under information described by Z-numbers for selecting online Bed and Breakfast (B&B) …

In the current intelligent era, high-dimensional multivariate time-series (HMTSs) data are
continuously monitored by heterogeneous devices from multiple observers in the Social …

We utilized a Python program to collect analysts' reports on the constituents of the CSI 300
(China Securities Index). From these reports, we extracted analyst ratings, readability, and …