The numerical simulation of non-smooth hybrid systems exhibiting chattering behavior requires high computational costs. In the worst case, the simulation appears to come to a halt, since infinitely many discrete transitions would need to be simulated. In this paper we present an FMI-based framework and prototypical implementation for robust and reliable detection and elimination “On the Fly” of...

We study a hybrid network traffic model that combines a fluid-based analytical model using ordinary differential equations with the packet-oriented discrete-event simulation. The hybrid model is important to large-scale real-time network simulations, where the packet-level emulation traffic is handled by discrete events and the majority of the background traffic is described more efficiently as...

This study proposes a hybrid model, which combines GARCH and Neural Network, for estimating VAR in Nasdaq 100 and Dow Jones futures index market. Empirical results demonstrated that the hybrid method has certain outperformed the conventional method (historical simulation, variance/covariance and the Monte Carlo simulation) in estimating VAR. In terms of accuracy, the hybrid method is superior t...

Light reflectance by semi-infinite turbid media is modeled by a hybrid of Monte Carlo simulation and diffusion theory, which combines the accuracy of Monte Carlo simulation near the source and the speed of diffusion theory distant from the source. For example, when the turbid medium has the following optical properties--absorption coefficient 1 cm-1, scattering coefficient 100 cm-1, anisotropy ...

Based on analysis of the configuration and powertrain parameters of the series hybrid electric bus typically operating in certain Chinese city, this paper establishes simulation model of the series hybrid powertrain. The energy efficiency and fuel economy of the series hybrid electric bus are analyzed by energy flow method in the driving cycles of Chinese typical city, Zhuzhou city in Hunan pro...

Conventional VAR (Value at Risk) estimation includes historical simulation, variance/covariance, and the Monte Carlo simulation method. This study is the first to present a hybrid method of estimating VAR, combining ARMA and Neural Network. Empirical results demonstrate that the hybrid method obtained superior results to the conventional method in estimating VAR. In terms of accuracy, both the ...

Process simulation is an increasingly useful tool for the analysis of processes in the mineral industry. The ability to simulate process behavior without having to disturb plant operation prevents the loss of man-hours and production. Additionally, simulation tools provide a platform for the development of control and optimization strategies. Model predictive control, in particular, relies heav...

Hybrid systems those composed of the interaction of discrete and continuous inputs outputs states and dynamic equations are an important class of models of complex real world phenomena However the simulation tools currently available seem to be ad hoc retro tting of existing packages hastily built new languages or specialized software for particular sub classes e g piecewise constant dynamics O...