The temporal evolution of nearshore sandbars (alongshore ridges of sand fringing coasts in water depths less than 10 m and of paramount importance for coastal safety) is commonly predicted using process-based models. These models are autoregressive and require offshore wave characteristics as input, properties that find their neural network equivalent in the NARX (Nonlinear AutoRegressive model...

Fusion prognostic framework for lithium-ion battery remaining useful life (RUL) estimation has become a hot spot. Especially, the cycle life prediction has been conducted widely, for which many prognostic methods have been proposed correspondingly. However, many fusion frameworks which can achieve high precision are accompanied with high computing complexity and high time consumption which make...

It has been found that the response of acupuncture point on the human meridian line exhibits nonlinear dynamic behavior when excitation of electroacupuncture is implemented on another meridian point. This nonlinear phenomenon is in fact a hysteretic phenomenon. In order to explore the characteristic of human meridian and finally find a way to improve the treatment of diseases via electro-acupun...

This paper gives necessary and sufficient conditions for stationarity and existence of second moments in mixtures of linear vector autoregressive models with autoregressive conditional heteroskedasticity. Sufficient conditions are also provided for a more general model in which the mixture components are permitted to exhibit limited forms of nonlinearity. When specialized to the corresponding n...

The problem of constructing data-based, predictive, reduced models for the KuramotoSivashinsky equation is considered, under circumstances where one has observation data only for a small subset of the dynamical variables. Accurate prediction is achieved by developing a discrete-time stochastic reduced system, based on a NARMAX (Nonlinear Autoregressive Moving Average with eXogenous input) repre...

Dryer system is a controlled plant which is normally used in chemical industry. The proper modeling of this system facilitates its maintenance and keeping. Normally this is not an easy task, unless having a complete model of the process, due to sudden and nonlinear events. In this paper the linear identification of dryer plant in Arak petroleum, is introduced according to the Autoregressive wit...

This paper explores nonlinear dynamics for the time series of the short term interest rate in the United States. The proposed model is an autoregressive threshold model augmented by conditional heteroskedasticity. The performance of the model is evaluated by considering its implications for the term structure of interest rates. The nonlinear dynamics imply a form of nonlin-earity in the levels ...

In this paper, Hammerstein model and Nonlinear AutoRegressive with eXogeneous inputs (NARX) model are used to represent tubular heat exchanger. Both models have been identified using least squares support vector machines based algorithms. Both algorithms were able to model the heat exchanger system without requiring any apriori assumptions regarding its structure. The results indicate that the ...