Time series forecasts are used to predict a future value or a classification at a particular point in time. Here’s a brief overview of their common uses and how they are developed. Industries from ...

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 ...

A range of national meteorological services across Europe and ECMWF have launched Anemoi, a framework for creating machine learning (ML) weather forecasting systems. Named after the Greek gods of the ...

In the ever-evolving landscape of capital infrastructure projects, government agencies find themselves performing an intricate dance. The heightened focus on the timely and budget-conforming ...

The Covid-19 pandemic has proved that history no longer repeats itself when it comes to understanding consumer behavior. Demand forecasting systems have been ill-equipped to address disruptions to our ...

Time series graphs are intuitive, helping you relate a metric to time. Marketing analysts are often faced with choosing a data visualization that speaks to managers and colleagues interested in ...

The authors analyze the interest rate risk in the banking book regulations, arguing that financial institutions must develop robust models for forecasting ...

Picture a single forecasting mistake triggering a cascade of negative consequences, such as surplus inventory, strained supplier relationships and disappointed customers. In today's world, accurate ...