australian rainfall is related with numerous key climate predictors namely el-nino southern oscillation (enso), indian ocean dipole (iod) and southern annular mode (sam). some studies have tried to discover the effects of these climate predictors on rainfall variability of different parts of australia, particularly western australia, queensland and victoria. nonetheless, clear association betwe...

It has been deemed as an effective tool of forecasting performance improvement to combine different component forecasting models. However, current nonlinear combining models are not able to meet the requirement of high forecasting accuracy in practice. To tackle this challenge, this paper constructs a hybrid, named genetic programming and least squared estimation based nonlinear combining metho...

This paper presents Multivariate-Factors fuzzy time series model for improving forecasting accuracy. The proposed model is based on fuzzy clustering and it employs eight main procedures to build the multivariate-factors model. The model is evaluated by studying the Egypt Wheat imports as a forecasting problem. Forecasting Egypt wheat imports depend on three factors: population size, wheat area,...

Combination forecasting takes all characters of each single forecasting method into consideration, and combines them to form a composite, which increases forecasting accuracy. The existing researches on combination forecasting select single model randomly, neglecting the internal characters of the forecasting object. After discussing the function of cointegration test and encompassing test in t...

The objective of this study was to model seasonal behavior of broiler price in Iran that can be used to forecast the monthly broiler prices. In this context, the periodic autoregressive (PAR), the seasonal integrated models, and the Box-Jenkins (SARIMA) models were used as the primary nominates for the forecasting model. It was shown that the PAR (q) model could not be considered as an appropri...

Wind forecasting is critical in the wind power industry, yet forecasting errors often exist. In order to effectively correct the forecasting error, this study develops a weather adapted bias correction scheme on the basis of an average bias-correction method, which considers the deviation of estimated biases associated with the difference in weather type within each unit of the statistical samp...

three combination methods commonly used in tourism forecasting are the simple average method, the variance-covariance method and the discounted msfe method. these methods assign the different weights that can not change at each time point to each individual forecasting model. in this study, we introduce the iowga operator combination method which can overcome the defect of previous three combin...

A multiphysics and a stochastic kinetic-energy backscatter scheme are employed to represent model uncertainty in a mesoscale ensemble prediction system using the Weather Research and Forecasting model. Both model-error schemes lead to significant improvements over the control ensemble system that is simply a downscaled global ensemble forecast with the same physics for each ensemble member. The...