The modeling methodology of tilting train is studied. The vehicle and pantograph are considered as nonlinear multiple rigid body systems, and the catenary is modeled by FEM method. The electrical mechanical actuators for carbody and pantograph tilting control are also considered in the tilting train model. The method of on-line curving detection, filtering and control is adopted for the tilting...

the purpose of this paper is to studying nonlinear k-ε turbulence models and its advantages in internal combustion engines, since the standard k-ε model is incapable of representing the anisotropy of turbulence intensities and fails to express the reynolds stresses adequately in rotating flows. therefore, this model is not only incapable of expressing the anisotropy of turbulence in an engine c...

An electric arc furnace (EAF) is known as nonlinear and time variant load that causes power quality (PQ) problems such as, current, voltage and current harmonics, voltage flicker, frequency changes in power system. One of the most important problems to study the EAF behavior is the choice of a suitable model for this load. Hence, in this paper, a probabilistic three-phase model is proposed base...

Several recent papers have developed neural network program synthesizers by using supervised learning over large sets of randomly generated programs and specifications. In this paper, we investigate the feasibility of this approach for program repair: given a specification and a candidate program assumed similar to a correct program for the specification, synthesize a program which meets the sp...

Non-linear dynamical systems are difficult to control due to the model uncertainties and external disturbances that may occur in these systems. This paper addresses the problem of identification using dynamic neural networks (DNNs) based on genetic algorithm (GA) for nonlinear dynamic systems. Four different dynamic neural networks are used for identification of the same nonlinear dynamic syste...

Two trains of light pulses at periods that are equally shifted from the harmonics of a missing fundamental are combined in a nonlinear crystal. As a result of a noncollinear phase-matched second-order nonlinear generation, a new train of pulses is obtained. When the temporal width of the input pulses is large, the frequency of the resulting pulse train follows the observations from classical ex...

The Z-scan technique has been used to study the nonlinearities of a variety of photosensitive materials. In resonant condition, the excited states determine the nonlinear properties. Using a Qswitched and modelocked Nd:YAG laser, that delivery trains with about 20 strong modelocked pulses with 70ps duration spaced by 13ns at 532 nm, we are able to resolve the dynamic of several nonlinear effect...

Usually, it is necessary for nonlinear online learning algorithms to store a set of misclassified observed examples for computing kernel values. For large-scale problems, this is not only time consuming but leads also to an out-of-memory problem. In the paper, a nonlinear online classification algorithm is proposed with a probability margin to address the problem. In particular, the discriminan...

Learning statistical models of nonlinear dynamical systems has long been an important problem in machine learning. The problem becomes especially hard when the dynamical system is composed of a mixture of nonlinear models, not just a single nonlinear model. To address this general case of nonlinear time-series modeling, we propose a new hierarchical architecture: the Trajectory Mixture Model (T...