Container throughput forecasting is critical for optimising port operations and maintaining the efficiency of global supply chains. Recent advances in machine learning have enabled researchers to ...

The partners in Lantern, a machine learning software firm focused on product distribution, pitched the technology to HVACR ...

Recent advances in forecasting demand within emergency departments (EDs) have been bolstered by the integration of machine learning and time series analytical techniques. The objective of these ...

Machine learning models are taking over in the field of weather forecasting, from a quick “how long will this rain last” to a 10-day outlook, all the way out to century-level predictions. The ...

Forecasting inflation has become a major challenge for central banks since 2020, due to supply chain disruptions and economic uncertainty post-pandemic. Machine learning models can improve forecasting ...

Researchers in China have applied a machine learning technology based on temporal convolutional networks in PV power forecasting for the first time. The new model reportedly outperforms similar models ...

Read more about From disease detection to biomass forecasting: AI improves aquaculture risk strategy on Devdiscourse ...

Ph.D. student Phillip Si and Assistant Professor Peng Chen developed Latent-EnSF, a technique that improves how ML models assimilate data to make predictions.

One of the unwritten axioms of data scientists specializing in machine learning methodologies is that they all try their hand at predicting the stock market. Some of the best attempts have turned a ...

Machine learning is a multibillion-dollar business with seemingly endless potential, but it poses some risks. Here's how to avoid the most common machine learning mistakes. Machine learning technology ...