A new framework for Experimental Design in Earth Sciences using Bayesian Evidential Learning (BEL4ED)

01 January 2019 → 31 December 2022
Regional and community funding: Special Research Fund
Research disciplines
  • Natural sciences
    • Hydrogeology
    • Geophysics not elsewhere classified
  • Engineering and technology
    • Water resources management
    • Modelling and simulation
experimental design optimum design uncertainty quantification hydrogeology geophysics Bayesian Evidential Learning
Project description

Earth Sciences predictions are facing large uncertainty related to the complexity and the lack of knowledge of the subsurface. Acquiring the most informative data set to reduce uncertainty is therefore highly valuable. However, its identification rapidly becomes intractable for large scale
problems. We propose to stochastically solve this problem under large uncertainty using our newly developed Bayesian Evidential Learning framework.