Bayesian prediction of solar flares
Large solar flares pose risks to our local space weather environment but they occur unpredictably; this project aims to improve flare prediction using Bayesian methods.
The largest solar flares produce hazardous "space weather" conditions near the Earth. They appear to occur at random, but there are many indicators that flares might occur. Can we combine these indicators to make a more accurate forecast? What limits the predictability of flares? This project will apply state-of-the-art techniques from Bayesian inference to these key problems.
Suitable for: Honours or Ph.D.
Techniques involved in the project: Bayesian theory, Markov chain Monte-Carlo methods, predictive discrimination, numerical methods, data analysis, visualisation
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The opportunity ID for this research opportunity is: 724
Other opportunities with Associate Professor Mike Wheatland