It is essential to find solar predictive methods to massively insert renewable energies on the electrical distribution grid. The goal of this study is to find the best methodology allowing predicting with high accuracy the hourly global radiation. The knowledge of this quantity is essential for the grid manager or the private PV producer in order to anticipate fluctuations related to clouds occ...

To solve the problem in which the conventional ARMA modeling methods for gyro random noise require a large number of samples and converge slowly, an ARMA modeling method using a robust Kalman filtering is developed. The ARMA model parameters are employed as state arguments. Unknown time-varying estimators of observation noise are used to achieve the estimated mean and variance of the observatio...

Zoonosis refers to the transmission of infectious diseases from animal to human. The increasing number of zoonosis incidence makes the great losses to lives, including humans and animals, and also the impact in social economic. It motivates development of a system that can predict the future number of zoonosis occurrences in human. This paper analyses and presents the use of Seasonal Autoregres...

India is basically an agricultural country and the success or failure of the harvest and water scarcity in any year is always considered with the greatest concern. The average annual or seasonal rainfall at a place does not give sufficient information regarding its capacity to support crop production. Rainfall distribution pattern is the most important. The rainfall forecasting is scientificall...

The robust self-tuning regulator of a class of linear systems, which can be described by the input-output Auto-Regressive Moving Average with exogenous (ARMAX) mathematical model with unknown and time-varying parameters, at bounded external disturbances is developed. A scheme of polynomial approximation has been applied to approximate the unknown and time-varying parameters of systems. The modi...

BACKGROUND Outbreaks of hand-foot-mouth disease (HFMD) have been reported for many times in Asia during the last decades. This emerging disease has drawn worldwide attention and vigilance. Nowadays, the prevention and control of HFMD has become an imperative issue in China. Early detection and response will be helpful before it happening, using modern information technology during the epidemic....

In this paper, modeling of doubly fed induction generator (DFIG) based wind energy conversion system (WECS) and speed controller are presented. The System Identification Toolbox MatLab is used to develop the linear model WECS by considering as input output. Two models, namely Auto Regressive with eXogenous Input (ARX) Auto-Regressive Moving Average (ARMAX), estimated. We ARX221 structure best f...

Harvesting energy from solar radiation has emerged as an effective approach to prolong the lifetime of outdoor harvesting sensor networks. The harvested must be carefully managed ensure that sufficient is available when scarce. For prediction problem power harvesting, this paper proposes adaptive seasonal auto-regressive integrated moving average model (ASARIMA) for prediction. A training set c...

I will report on a study of the usefulness of ARMA time scale algorithms to synchronize clocks on a digital network. The algorithm acquires periodic time differences between a local system clock and a remote time server by means of any of the standard message formats such as the format used by the Network Time Protocol. It models the current time difference as a linear combination of previous t...

b a c k g r o u n d & aim: one of the common used models in time series is auto regressive integrated moving  average  (arima)  model.  arima  will  do  modeling  only  linearly.  artificial  neural networks (ann) are modern methods that be used for time series forecasting.  these models can identify non-linear relationships  among data. the breast cancer has the most mortality of cancers among...