Feedback versus uncertainty

Even without uncertainty about the model structure or parameters, the output of a hydrological model run still contains several sources of uncertainty. These are: measurement errors affecting the input, the transition from continuous time and space to discrete time and space, which causes loss of information about the input, discretization of...

Interval Analysis: Contributions to static and dynamic optimization

The field of global optimization has been an active one for many years. By far the most applied methods are gradient and evolutionary based algorithms. The most appearing drawback of those types of methods is that one cannot guarantee that the global solution is found within finite time. Moreover, if the global solution is found (by chance), the...

Global Optimization using Interval Analysis: Interval Optimization for Aerospace Applications

Optimization is an important element in aerospace related research. It is encountered for example in trajectory optimization problems, such as: satellite formation flying, spacecraft re-entry optimization and airport approach and departure optimization; in control optimization, for example in adaptive control algorithms; and in system...

Neural Network Output Optimization Using Interval Analysis

The problem of output optimization within a specified input space of neural networks (NNs) with fixed weights is discussed in this paper. The problem is (highly) nonlinear when nonlinear activation functions are used. This global optimization problem is encountered in the reinforcement learning (RL) community. Interval analysis is applied to...