Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...

The latest study published in Engineering has unveiled a groundbreaking approach to advancing green ethylene manufacturing, with profound implications for global sustainable chemical production.

Abstract: dynamic multiobjective optimization (DMO) problems are prevalent in many practical applications and have garnered significant attention from both industry and academia, leading to the ...

This project uses reinforcement learning to optimize traffic signals, reducing congestion and improving flow through dynamic adjustments and simulation analysis. SynapticGrid is an AI-driven system ...

Objective: This study aimed to develop a risk prediction model for post-treatment oligometastasis in nasopharyngeal carcinoma (NPC) by integrating pathomics features and an improved Support vector ...

Unlock the secrets to smarter fleet routing - discover how dynamic route optimization can cut costs, boost efficiency, and help you adapt to real-world challenges. Learn how NextBillion.ai's Routing & ...

Learn how to implement Adam optimization from the ground up in Python! This step-by-step guide will walk you through the algorithm's mechanics and how to use it in machine learning projects. 🚀🐍 ...