The time series prediction of avian influenza epidemics is a complex issue, because avian influenza has latent seasonality which is difficult to identify. Although researchers have applied a neural network (NN) model and the Box-Jenkins model for the seasonal epidemic series research area, the results are limited. In this study, we develop a new prediction seasonal auto-regressive-based support...

Electric load forecasting is an important issue for a power utility, associated with the management of daily operations such as energy transfer scheduling, unit commitment, and load dispatch. Inspired by strong non-linear learning capability of support vector regression (SVR), this paper presents a SVR model hybridized with the empirical mode decomposition (EMD) method and auto regression (AR) ...

foreign trade of any country is considered as one of the major economic sectors of that society as far as some refer to trade as the “engine of growth”. foreign exchange rate and its volatilities is one of the effective factors determining foreign trade. the present paper deals with the impact of real exchange rate uncertainty on imports in iran during 1979-2009. in this respect, first, among v...

this paper investigates the forecasting performance of different time-varying bvar models for iranian inflation. forecast accuracy of a bvar model with litterman’s prior compared with a time-varying bvar model (a version introduced by doan et al., 1984); and a modified time-varying bvar model, where the autoregressive coefficients are held constant and only the deterministic components are allo...

In this paper we present a simple hierarchical Bayesian treatment of the sparse kernel logistic regression (KLR) model based on the evidence framework introduced by MacKay. The principal innovation lies in the re-parameterisation of the model such that the usual spherical Gaussian prior over the parameters in the kernel induced feature space also corresponds to a spherical Gaussian prior over t...