Abstract: Effective resource allocation in telecommunication networks can benefit from accurate demand forecasting to optimize performance and prevent inefficiencies such as resource over-provisioning ...

This code is the official PyTorch implementation of our KDD'25 paper: DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting. If you find this project helpful, please don't forget to give ...

Abstract: This paper explores the role of multivariate probabilistic forecasting in improving O-RAN operations, focusing on network sustainability aspects. A comprehensive analysis of its potential ...

HONG KONG, Jan 28 (Reuters) - A team of Hong Kong scientists has developed an artificial intelligence weather-forecasting system to predict thunderstorms and heavy downpours up to four hours ahead, ...

At the start of a new year, it’s human nature to want a crystal ball: What lies ahead, and how will it affect us? This feeling is particularly acute in times of uncertainty, when the ability to engage ...

Traditional long-term forecasting models are no longer sufficient as electrification, DER growth, EV adoption, extreme weather events and new large loads introduce unprecedented complexity. The future ...

Making precise numerical predictions is risky. No wonder most people prefer prognosticating in prose. But some less lily-livered forecasters are happy to commit themselves to specific numbers, such as ...

Will the world still need economists in 2030? With skin in the game, we certainly hope so — but artificial intelligence is already transforming economic analysis. In our own work — and in a review of ...

Every three months, participants in the Metaculus forecasting cup try to predict the future for a prize pot of about $5,000. Metaculus, a forecasting platform, poses questions of geopolitical ...

It was only a generation or two ago that weather forecasts were not to be taken too seriously: funny-guy meteorologists on the local news wisecracking about ruined golf plans. That has long stopped ...