Increasing quantities of active spacecraft and debris in the space environment pose substantial risk to the continued safety of specific orbit regimes. Successful quantification of space object state knowledge is a fundamental prerequisite in ensuring operational safety and continuity. However, uncertainty in orbit dynamics such as atmospheric drag, solar radiation pressure, and other effects c...

Evolutionary algorithms are general, randomized search heuristics that are influenced by many parameters. Though evolutionary algorithms are assumed to be robust, it is well-known that choosing the parameters appropriately is crucial for success and efficiency of the search. It has been shown in many experiments, that non-static parameter settings can be by far superior to static ones but theor...

There have been recently a considerable experimental and theoretical effort to characterize Spatiotemporal Chaos (STC) [Cross & Hohenberg, 1994; Gollub, 1994]. Weak STC seems to be an ubiquitous phenomenon in large non-equilibrium systems. In some cases STC arise in the proximity of threshold and can be described within the context of weakly nonlinear theories. These theories are well developed...

The American Academy of Allergy, Asthma and Immunology (AAAAI) and the American College of Allergy, Asthma and Immunology (ACAAI) have jointly accepted responsibility for establishing ‘‘Attaining optimal asthma control: A practice parameter.’’ This is a complete and comprehensive document at the current time. The medical environment is a changing environment, and not all recommendations will be...

On-line control of EA parameters is an approach to parameter setting that offers the advantage of values changing during the run. In this paper, we investigate parameter control from a generic and parameter-independent perspective. We propose a generic control mechanism that is targeted to repetitive applications, can be applied to any numeric parameter and is tailored to specific types of prob...

Every evolutionary algorithm needs to address two important facets: exploration and exploitation of a search space. Evolutionary search must combine exploration of the new regions of the space with exploitation of the potential solutions already identified. The necessity of balancing exploration with exploitation needs to be intelligent. This paper introduces an entropy-driven parameter control...

The adaptive output feedback control problem of chemical distributed parameter systems is investigated while the process parameters are unknown. Such systems can be usually modeled by semilinear partial differential equations (PDEs). A combination of Galerkin’s method and proper orthogonal decomposition is applied to generate a reduced order model which captures the dominant dynamic behavior of...

Optimization of the control parameters of genetic algorithms is often a time consuming and tedious task. In this work we take the meta-level genetic algorithm approach to control parameter optimization. We enhance this process by incorporating a neural network for tness evaluation. This neural network is trained to learn the complex interactions of the genetic algorithm control parameters and i...

Directed differentiation is the process which selectively induce differentiation of stem cells toward definitive cells, but how directed differentiation occurs when stem cells confront the external cues has not been established theoretically. We demonstrate here directed differentiation of a simplified two-component network by using systematic parameter perturbations. These methods and results ...

In this paper, the convergence of parameter estimates and the interactions among the two adaptive fuzzy systems constituting an indirect adaptive fuzzy controller are studied, both analytically and by means of simulations with a second-order nonlinear system. The analytical results and the simulations, performed with various initial conditions and learning rates, highlight how the interactions ...