abstract one of the major factors on the amount of water resources is river flow which is so dependent to the hydrologic and meteorologic phenomena. simulation and forecasting of river flow makes the decision maker capable to effectively manage the water resources projects. so, simulation and forecasting models such as artificial neural networks (anns) are commonly used for simulation and predi...

Optimal robust MPC for constrained linear systems that are subject to additive uncertainty requires a closed loop optimization with computation that rises exponentially with the prediction horizon, N . This was overcome by parameterized tube MPC (PTMPC) that used a triangular separable prediction strategy in which predictions are decomposed into a nominal and N − 1 partial prediction sequences,...

The polynomial chaos approach for stochastic simulation is applied to trajectory optimization, by conceptually replacing random variables with free variables. Using the gradient method, we generate with low computational cost an accurate parametrization of optimal trajectories.

The relative computational complexity of two free-variable labelled modal tableaux (KEM and Single Step Tableaux, SST) is investigated. We discuss the reasons why p-simulation is not a proper measure to compare tableaux-like proof systems, and we propose an improved comparison scale (p-search-simulation). It shown that KEM p-search-simulates SST while SST cannot p-search-simulate KEM.

A general theorem is proved which shows how a system of contending asynchronous processes with a special auxiliary supervisor process can be simulated by a system of contending processes without such a supervisor, with only a small increase in the shared space needed for communication. Two applications are presented, synchronization algorithms with different fairness properties requiring N + c ...

Diagnostics for normal errors in regression typically utilize ordinary residuals, despite the failure of assumptions to validate their use. Case studies here show that such misuse may be critical. A remedy invokes recovered errors having the required properties, taking into account that such errors are closer to normality than are disturbances in the observations themselves. Simulation studies ...

In the classical errors-in-variables problem, the goal is to estimate a regression curve from data in which the explanatory variable is measured with error. In this context, nonparametric methods have been proposed that rely on the assumption that the measurement errors are identically distributed. Although there are many situations in which this assumption is too restrictive, nonparametric est...