In our present study, GARCH family models are used for modeling and forecasting the rice yield of four provinces of Pakistan during the period of 1947-48 to 2008-09. Also Auto regressive, moving average and Autoregressive moving average models are described. Thus, the selected GARCH models for all provinces are also presented for forecasting purpose on the basis of two criteria AIC (Akaike info...

This paper presents a new method of self-sensing both of the displacement and the external applied force at the tip of piezoelectric cantilevers. Integrated electric current across piezoelectric actuators is compensated against material nonlinearities (creep, hysteresis) to provide reliable information. We propose to compensate the hysteresis by using the Prandtl-Ishlinskii static approach whil...

We have already developed a speech analysis method based on the Glottal-ARMAX (Auto Regressive and Moving Average eXogenous) model, in which the speech production model is supposed to be an ARMAX vocal tract model and two kinds of excitation: glottal source model excitation and white Gaussian. The speech analysis method based on the Glottal-ARMAX model can estimate the glottal source and ARMAX ...

In this paper, a simple neural network (NN) control scheme is developed for a class of discrete-time multi-input multi-output (MIMO) non-affine nonlinear systems with triangular form inputs and disturbances. The system studied is described by NARMAX (Nonlinear Auto Regressive Moving Average with eXogenous inputs) model. Firstly, by using implicit function theorem, the existence of the implicit ...

This paper presents a neural network predictive control strategy to optimize power distribution for a fuel cell/ultracapacitor hybrid power system of a robot. We model the nonlinear power system by employing time variant auto-regressive moving average with exogenous (ARMAX), and using recurrent neural network to represent the complicated coefficients of the ARMAX model. Because the dynamic of t...