rainfall-runoff is one of complex hydrological processes that is affected by a variety of physical and hydrological factors. in this study statistical method armax model, neural network, neuro-fuzzy (anfis subtractive clustering and grid partition) and two hybrid models of this methods were used to simulate rainfall-runoff and prediction of streamflow. in each method optimum structure was deter...

Internal model based temperature controllers are developed for effusion sources that are part of a continuous process for production of thin-film photovoltaic modules. Operation of this system in a research framework necessitates the ability to perform fast, overshoot-free reference changes. To address input constraints, controllers are implemented using an anti-windup scheme. Both empirical AR...

This paper examines numbers of acquisitions for the UK and demonstrates that actual values are predictable and the time-series properties for the series can also be established. A link between economic conditions and acquisition levels seems likely and such models can be easily produced. The economic factors and the time-series properties are then combined in an ARMAX model producing better res...

The handling of various input constraints in the self-tuning generalized predictive control (STGPC) problem of ARIMAX/ARMAX systems is considered. The methods based on the Lagrange multipliers and Lemke’s algorithm are used to solve the constrained optimization problem. A self-tuning controller is implemented in an indirect way, and the considered constraints imposed on the control input signal...

This paper develops high performance system identification and linearisation techniques, using a genetic algorithm. The algorithm is fine tuned by simulated annealing, which yields a faster convergence and a more accurate search. This global search technique is used to identify the parameters of a system described by an ARMAX model in the presence of white noise and to approximate a nonlinear m...

In what concerns extreme values modeling, heavy tailed autoregressive processes defined with the minimum or maximum operator have proved to be good alternatives to classical linear ARMA with heavy tailed marginals (Davis and Resnick [8], Ferreira and Canto e Castro [13]). In this paper we present a complete characterization of the tail behavior of the autoregressive Pareto process known as Yeh–...

the control of car following is essential due to its safety and its operational efficiency. for this purpose, this paper builds a model of car following behavior based on armax structure from a real traffic dataset and design a model predictive control (mpc) system. based on the relative distance and relative acceleration of each instant, the mpc predicts the future behavior of the leader vehic...