## Smarter Demand Forecasting for Fast Fashion: Hybrid Models for a Dynamic Market
[](https://events.vtools.ieee.org/event/register/476734)
- Date: **10 Apr 2025-**Time: **11:30 PM UTC to 01:00 AM UTC**
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### Hosts
- [Southwestern USA - Region 5](mailto:john.santiago@ieee.org?subject=Smarter%20Demand%20Forecasting%20for%20Fast%20Fashion%3A%20%20Hybrid%20Models%20for%20a%20Dynamic%20Market%20-%20Southwestern%20USA%20-%20Region%205 "mailto:john.santiago@ieee.org?subject=Smarter%20Demand%20Forecasting%20for%20Fast%20Fashion%3A%20%20Hybrid%20Models%20for%20a%20Dynamic%20Market%20-%20Southwestern%20USA%20-%20Region%205")
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- Forecasting the demand for new fashion products in the fast fashion industry is a com-
plex task due to its dynamic nature, short product life cycles, and limited historical data.
Traditional forecasting models often fail, leading to inefficiencies such as overproduc-
tion or underproduction. This paper reviews key challenges and explores innovative
machine learning (ML) and artificial intelligence (AI)-based models to improve fore-
cast accuracy. We propose a hybrid AI-driven approach that integrates structured and
unstructured data sources, real-time monitoring, and ensemble models to address fore-
cast limitations in the fast fashion industry.
[https://events.vtools.ieee.org/event/register/476734](https://events.vtools.ieee.org/event/register/476734)
