Nonlinearity & Predictability

Analysis of the impact nonlinearity and structural model error have on simulation-based predictability, detection, control, uncertainty quantification (UQ) and insight into actual systems whose dynamics are best described by nonlinear models. “All models are wrong;” presentation of methods for detecting how/when they fail. Introduction to a geometric view of dynamics, language and limitations of nonlinear dynamics and chaos. Resource allocation in the design and construction of nonlinear prediction/automated decision systems. The role of model-based probability(s) in real time monitoring, decision-making and policy/regulatory guidance. Comparison, evaluation and deep-combination of competing probabilistic engines. Implications for UQ in applications including guidance, AI, automated machinery, disaster risk reduction and sports. Pre: Graduate Standing.