IEEE

Temporal Preprocessing and Ensemble Learning for Real-Time Fault Detection in Chemical Process Systems: A Data-Driven Approach on Tennessee Eastman Benchmark

Abstract: Chemical process industries require robust fault detection systems to ensure operational safety, product quality, and environmental compliance. However, existing methods face three critical ...
Tech Xplore

A simple baseline for AI forecasting in machine learning

In a recent paper, SFI Complexity Postdoctoral Fellow Yuanzhao Zhang and co-author William Gilpin show that a deceptively ...
Frontiers

Leveraging Artificial Intelligence and Real World Data for Novel Insights in Healthcare.

This issue aims to showcase how machine learning (ML) and Artificial Intelligence (AI) approaches can be used with real world data (RWD) sources to generate ...
Tech Xplore

Compression technique makes AI models leaner and faster while they're still learning

Training a large artificial intelligence model is expensive, not just in dollars, but in time, energy, and computational ...
Frontiers

The Neuro Bureau Preprocessing Initiative: open sharing of preprocessed neuroimaging data and derivatives

Grass-roots initiatives such as the 1000 Functional Connectomes Project (FCP) and International Neuroimaging Data- sharing Initiative (INDI) [1] are successfully amassing and sharing large-scale brain ...
News-Medical.Net

Interpretable machine learning model advances analysis of complex genetic traits

A new study published in Genome Research presents an interpretable artificial intelligence framework that improves both the accuracy and transparency of genomic prediction, a key challenge in fields ...