[Cite as http://purl.org/au-research/grants/arc/DP140101366]
Researchers Prof Jie Lu; A/Prof Guangquan Zhang; Prof Dr Witold Pedrycz;
Brief description Collecting sufficient up-to-date data to train a learning model for data analysis and prediction is difficult and expensive. This project will develop a Fuzzy Transfer Learning methodology, using Information Granularity theory, that exploits data with different features and/or distributions available in other, similar systems, to provide accurate learning-based prediction for current problems. It will establish a new research direction, Fuzzy Transfer Learning for Prediction, and the outcomes will enable government and industry to better use past experience to make more accurate predictions and decisions. Highly significant benefits will also accrue in the data analytics, business intelligence and decision making research fields.
Funding Amount 394000
Funding Scheme Discovery Projects