Observability in dynamic evolutionary models

Observability and the eigenstructure of multivariate canonical dynamic linear models

Multivariate canonical state space dynamic models are developed by studying the eigenstructure of their transition matrices. Observability is introduced for time-varying model components defining locally observable dynamic models. Single component models that have a simple transition matrix are first discussed and categorized according to their forecast function. Then more complicated models, d...

Optimization in Uncertain and Complex Dynamic Environments with Evolutionary Methods

In the real world, many of the optimization issues are dynamic, uncertain, and complex in which the objective function or constraints can be changed over time. Consequently, the optimum of these issues is changed nonlinearly. Therefore, the optimization algorithms not only should search the global optimum value in the space but also should follow the path of optimal change in dynamic environmen...

Evolutionary Optimization with Dynamic Fidelity Computational Models

In this paper, we propose an evolutionary framework for model fidelity control that decides, at runtime, the appropriate fidelity level of the computational model, which is deemed to be computationally less expensive, to be used in place of the exact analysis code as the search progresses. Empirical study on an aerodynamic airfoil design problem based on a Memetic Algorithm with Dynamic Fidelit...

Tracking of Dynamic Physical Systems with Dynamic Bayesian Net Models Factored using Structural Observability

Monitoring, diagnosis, and control of complex physical systems require tracking their dynamic behavior during system operation. Effective tracking requires an accurate system behavior model, and sufficient measurements to estimate system state. However, models suffer from lack of accuracy, and measurements are noisy, making the tracking task difficult. Dynamic Bayes Nets (DBNs) provide a genera...

On the Dynamic Foundation of Evolutionary Stability in Continuous Models