Complex Time-series System Forecasting Reinforced by Expert Knowledge
Published:
- Funding: $428,331 AUD in cash.
- Investigator: Hung Le
- Role: Sole Principle Investigator.
- Abstract: This project aims to predict complex behaviours of multiple interconnected data streams, introducing a new forecasting framework compatible with big data and domain knowledge. It expects to provide actionable insights for informed decision-making, fostering the development of robust forecasting models crucial for Australia’s leadership in the global AI era. Anticipated outcomes include more accurate predictions in critical domains like healthcare, potentially saving lives, and material science, expediting material discovery. The project should advance time-series prediction research, contributing to economic growth, environmental benefits, improved social well-being, and fostering commercial growth via innovative forecasting capabilities.