The number of aquaculture households in Palembang City continues to increase from 2017 only 682 1,050 2018. But on the contrary terms amount production, total production decreased by 24,259 tons 2014 and 20,327 (BPS, 2018). One steps that can be taken determine condition is doing forecasting. This useful for knowing or predicting results with precise accuracy. study aims prediction using Autore...

OBJECTIVE Injury is currently an increasing public health problem in China. Reducing the loss due to injuries has become a main priority of public health policies. Early warning of injury mortality based on surveillance information is essential for reducing or controlling the disease burden of injuries. We conducted this study to find the possibility of applying autoregressive integrated moving...

Finansal verilerin en dikkate değer özelliklerinden biri zamana bağlı biçimde bir dizi teşkil etmeleridir. Bundan ötürü zaman serilerinin unsurları, söz konusu ifade ettiği ekonomik ve finansal parametreler hakkındaki bilgiyi de kapsamaktadır. Finans çalışmalarında değişkenlere ilişkin öngörü ya da tahmin hayati öneme sahiptir. değişkenlerin doğru, sağlıklı edilebilmesi, piyasalardaki paydaşlar...

A renormalization group analysis is applied to autoregressive processes with an infinite series of coefficients. A simple fixed point is given by a random walk, and a second class is found that is proportional to the high order coefficients of fractional autoregressive integrated moving average (ARIMA) processes. The approach might be useful to detect nonstationarity in autoregressive processes.

Time series of quarterly observations on Gross Domestic Product (GDP) is collected and used in this study. Forecasting results of ANNs are compared with those of the Autoregressive Integrated Moving Average (ARIMA) and regression as benchmark methods. Using Root Mean Square Error (RMSE), the empirical results show that ANN performs better than the traditional methods in forecasting GDP.

drought is random and nonlinear phenomenon and using linear stochastic models, nonlinear artificial neural network and hybrid models is advantaged for drought forecasting. this paper presents the performances of autoregressive integrated moving average (arima), direct multi-step neural network (dmsnn), recursive multi-step neural network (rmsnn), hybrid stochastic neural network of directive ap...

Both the fractional Brownian motion (fBm) and the Autoregressive Integrated Moving Average (ARIMA) models have been applied to teletraffic scenarios in recent years. These models became popular after the discovery that Ethernet and VBR video data appear to possess the property of selfsimilarity. However the results presented in this paper suggest that Ethernet data is more impulsive than traffi...