Most AI tools are working with incomplete, siloed data, giving leaders a fragmented view of their own interconnected business ...

Less instrumentation. More insight. Physics-informed virtual sensors are shifting condition monitoring from isolated pilots ...

Streetline is now inviting state Departments of Transportation, freight offices, and transportation planning agencies to ...

Implementing predictive analytics can become one of the biggest competitive differentiators for any educational institution ...

North America held a dominant market position, capturing more than a 36.1% share, holding USD 28.38 billion in revenue.

UBS leverages algorithmic pricing, machine learning, and advanced volatility modeling to deliver reliable FX execution across ...

A new research paper shows the approach performs significantly better than the random-walk forecasting method.

Barnes & Thornburg attorneys Lauren Baker and John W. Cox examine the practical uses, benefits, and challenges of using ...

In the past decade, cloud-scale analytics tools have transformed the digital fight against deforestation. Instead of manual ...

Background: Machine learning (ML) has been investigated for its predictive value in knee osteoarthritis (KOA) progression. However, systematic evidence on the effectiveness of ML is still lacking, ...

Abstract: Accurate Short-Term Load Forecasting (STLF) is essential for effective operational planning, particularly for optimizing maintenance schedules, managing power generation capacity, and ...