Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

The line between human and artificial intelligence is growing ever more blurry. Since 2021, AI has deciphered ancient texts ...

Abstract: With the booming rural economy and the deepening of digital transformation, accurately understanding the behavioral patterns of rural consumers has become a key issue that companies and ...

Introduction: Accurate identification of forest tree species is essential for sustainable forest management, biodiversity assessment, and environmental monitoring. Urban forests, in particular, ...

ABSTRACT: This study presents a comparative analysis of machine learning models for threat detection in Internet of Things (IoT) devices using the CICIoT2023 dataset. We evaluate Logistic Regression, ...

In this study, multi-source remote sensing data and machine learning algorithms were used to delineate the prospect area of remote sensing geological prospecting in eastern Botswana. Landsat 8 remote ...

Abstract: This research aims to compare the performance of Logistic Regression and Random Forest algorithms in classifying cyber-attack types. Using a data set consisting of 494,021 data points with ...

Cardiovascular disease (CVD) is one of the leading causes of death worldwide, and answers are urgently needed regarding many aspects, particularly risk identification and prognosis prediction.