Oversimplifies trends and ignores real-world disruptions. Can’t predict economic downturns, competitor actions and shifts in customer behavior on its own. Ignores randomness; every forecast will have ...

This project implements state-of-the-art deep learning models for financial time series forecasting with a focus on uncertainty quantification. The system provides not just point predictions, but ...

Abstract: Forecasting the photovoltaic (PV) power generation plays a key role in facilitating the grid integration of the technology by reducing the amount and cost of imbalances caused by the ...

Many government contractors still rely on fragmented systems and static spreadsheets to project what’s ahead. That approach may work for tracking awarded contracts, but it fails to support confident ...

Not all risks come from storms—some stem from political and economic shifts. For some, change means opportunity; for others, uncertainty. With the election behind us, how can we navigate risk beyond ...

Supply chain forecasting is becoming an increasingly critical component of operational success. Accurate forecasting enables companies to optimize inventory levels, reduce waste, enhance customer ...

Supply chain planningis almost impossible without having an understanding of the future. And since an ecommerce supply chain consists of several moving parts, how does an online brand go about supply ...