modelling and forecasting stock market is a challenging task for economists and engineers since it has a dynamic structure and nonlinear characteristic. this nonlinearity affects the efficiency of the price characteristics. using an artificial neural network (ann) is a proper way to model this nonlinearity and it has been used successfully in one-step-ahead and multi-step-ahead prediction of di...

in the present study, the nonlinear model of non-newtonian blood flow in cosine-shape stenosed elastic artery is numerically examined. the model is carried out for axisymmetric, two-dimensional and fully developed blood flow. the vessel wall is assumed to be have time-dependent radius that is important factor for study of blood flow. the cosine-shape stenosis convert to rigid artery by using a ...

nonlinear hunting speeds of railway vehicles running on a tangent track are analytically obtained using hopf bifurcation theory in this paper. the railway vehicle model consists of nonlinear primary yaw dampers, nonlinear flange contact stiffness as well as the clearance between the wheel flange and rail tread. linear and nonlinear critical speeds are obtained using bogoliubov method. a compreh...

Nonlinear hunting speeds of railway vehicles running on a tangent track are analytically obtained using Hopf bifurcation theory in this paper. The railway vehicle model consists of nonlinear primary yaw dampers, nonlinear flange contact stiffness as well as the clearance between the wheel flange and rail tread. Linear and nonlinear critical speeds are obtained using Bogoliubov method. A compreh...

Nonlinear problems are more challenging and almost complex to be solved. A recently developed Homotopy Perturbation Method (HPM) is introduced. This method is used to represent the system as a less complicated (almost linear) model. To verify the effectiveness, HPM based model is compared with the nonlinear dynamic in both open and closed loop PI controlled. The error indices are approximation ...

A new approach for pole placement of nonlinear systems using state feedback and fuzzy system is proposed. We use a new online fuzzy training method to identify and to obtain a fuzzy model for the unknown nonlinear system using only the system input and output. Then, we linearized this identified model at each sampling time to have an approximate linear time varying system. In order to stabilize...