A linear Markov system can be represented by an autoregressive and moving average (ARMA) model in discrete time domain. It can be used to identify some system model and its associated parameters. Recently, the ARMA model has been extended to an ARMA-LiNGAM model which is a canonical form to represent the system. It is expected to provide more detailed information of the model structure and the ...

This paper presents an improvement of hybrid of nonlinear autoregressive with exogenous input (NARX) and autoregressive moving average (ARMA) for long-term machine state forecasting based on vibration data. In this study, vibration data is considered as a combination of two components which are deterministic data and error. The deterministic component may describe the degradation index of machi...

Using the multiple threshold autoregressive and moving average (TARMA) model we analyze the nonlinearities in the dynamics of realized volatilities of daily stock returns of 30 companies in the Dow Jones index. We find that the realized volatility processes can be characterized by the high, moderate, and low regimes and that the persistence, variance and ARMA error term change with each regime....

The combination forecasting model IOWGA-EMD-ARMA-WNN is proposed in this paper. The randomness, periodicity and tendency of the original data are showed by EMD decomposition in EMD-ARMA model. WNN combines the advantages of wavelet analysis and BP neural network and improves the learning efficiency and forecasting accuracy. The weight of combination model is decided by forecasting precision of ...

With the increase of wind power as a renewable energy source in many countries, wind speed forecasting has become more and more important to the planning of wind speed plants, the scheduling of dispatchable generation and tariffs in the day-ahead electricity market, and the operation of power systems. However, the uncertainty of wind speed makes troubles in them. For this reason, a wind speed f...

the artificial accelerograms have been developed for assessing the dynamic response ofstructures. considering seismological properties of the site are necessary for the best simulation ofaccelerograms. the real recorded accelergrams for simulating earthquake phenomenon are used in thearma model. this is due to the fact that the arma model can be considered more advantageous than theothers.in th...

In this research, monthly rainfall of Shiraz synoptic station from March 1971 to February 2016 was studied using different time series models by ITSM Software. Results showed that the ARMA (1,12) model based on Hannan-Rissanen method was the best model which fitted to the data. Then, to assess the verification and accuracy of the model, the monthly rainfall for 60 months (from March 2011 to Feb...

Often exploration seismic data lacks low and high frequency band signals. The low frequency information provides crucial information about the mean model. Thus, estimation of absolute models using inversion schemes is difficult in case of band limited seismic data. We present a new method to synthesize initial model for inversion of seismic data using autoregressive and moving average modeling....