Machine learning is transforming how crypto traders create and understand signals. From supervised models such as Random Forests and Gradient Boosting Machines to sophisticated deep learning hybrids ...
Wang, Z. (2025) Research on Prediction of Air Quality CO Concentration Based on Python Machine Learning. Advances in Internet ...
AZoRobotics on MSN
AI Algorithm Boosts Accuracy of Satellite-Based Oil Spill Monitoring
James Cook University researchers have created an AI tool that integrates satellite imagery, improving oil spill detection ...
Demand forecasting remains one of the most complex challenges in retail management. As consumer behavior evolves rapidly, ...
Researchers from the University of South Florida and partner institutes developed the DynBAS-AWRF Tree, an AI-powered, energy ...
Abstract: This research aims to formulate an optimal control algorithm for a hydrothermal air-conditioning system, with the objective of minimizing energy consumption while simultaneously ensuring ...
Abstract: The risk of pedestrian-involved traffic accidents represents a significant challenge to road safety and necessitates objective methods for analyzing the contributing factors. This study ...
A comprehensive machine learning web application that predicts disease risk based on patient medical parameters using Logistic Regression and Random Forest algorithms. This project provides an ...
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, ...
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