In today's global economy, the need for resilient supply chains has never been greater. Organizations must continuously adapt ...

While multiple machine learning (ML) algorithms offered similar predictive performance, the cost-effective analysis revealed ...

When every team can use data to make smarter decisions, the playing field is leveled and the door opens to a more innovative, ...

New data-driven tools give employers an edge in preventing injuries, improving compliance, and optimizing safety protocols before accidents occur.

The least absolute shrinkage and selection operator-logistic regression (Lasso-LR) model is optimal for predicting ...

An expert in analytics-driven transformation presents an in-depth exploration of the technical integration of analytics ...

Soil liquefaction—the process where saturated soil loses its structure and transforms to a fluid-like state—can have ...

Early prediction of in-hospital pneumonia mortality can effectively be done using a machine learning (ML) model based on clinical data.

1. Regression analysis. Regression models are the mainstay of predictive analytics. The linear regression model analyzes the relationship between the response or dependent variable and a set of ...

These models provide the clarity necessary for evidence-based decision making, allowing officials to anticipate outbreaks and respond effectively. Strengthening the predictive analytics ...