Abstract
The University of Central Florida invention is an agent-enabled deep-learning algorithm to forecast COVID-19 positive cases with a greater degree of accuracy. The invention provides an agent learner architecture and methods to boost the capabilities of deep learning algorithms for accuracy in forecasting challenging pandemic scenarios like COVID-19. The technology also has potential applications with data-heavy sets for analysis (for example, financial markets).
Partnering Opportunity
The research team is seeking partners for licensing and/or research collaboration.
Stage of Development
Prototype available.
Benefit
Results in fewer COVID-19 forecast errors compared to other agent architecturesBoosts the capabilities of deep learning models like bi-directional long short term memory (BILSTM)Market Application
COVID-19 pandemic forecastingGlobal warming forecastingStock market predictions
Brochure
