Quantification, optimisation, and application of deep uncertainty. This project aims to develop a framework for deep uncertainty quantification. There is currently a fundamental gap between deep learning research and the methods required to quantify and manage uncertainties. The research will propose a novel distribution-free methodology to generate deep predictive uncertainty estimates to avoid the assumptions of existing methods. The quality of estimates will be enhanced by applying an interva ....Quantification, optimisation, and application of deep uncertainty. This project aims to develop a framework for deep uncertainty quantification. There is currently a fundamental gap between deep learning research and the methods required to quantify and manage uncertainties. The research will propose a novel distribution-free methodology to generate deep predictive uncertainty estimates to avoid the assumptions of existing methods. The quality of estimates will be enhanced by applying an interval-based adversarial training step. The project is expected to help data-driven Australian organisations and industries to better quantify and manage forecasting uncertainties. This project will provide them with significant cost savings through better decision making and more robust planning.Read moreRead less
An investigation of the impacts of increased power supply to the national grid by wind generators on the Australian electricity industry. The aim of this project is to discover the most economical and effective way to accommodate large increases in wind power into the national grid and to understand the effects on the national electricity market. This is crucial to ensure stability of electricity supply and affordable prices in the transition towards a low carbon economy.