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...

The problem of accurately determining river flows from rainfall, evaporation and other factors, occupies an important place in hydrology. The rainfall-runoff process is believed to be highly non-linear, time varying, spatially distributed and not easily described by simple models. Practitioners in water resources have embraced data-driven modelling approaches enthusiastically, as they are perce...

This paper presents a novel framework for the complexity analysis of rainfall, runoff, and runoff coefficient (RC) time series using multiscale entropy (MSE). The MSE analysis of RC time series was used to investigate changes in the complexity of rainfallrunoff processes due to human activities. Firstly, a coarse graining process was applied to a time series. The sample entropy was then compute...

abstract in this study we have used the monthly data resulted from the calculation of temperature and precipitation for a 52-year period (1951-2003). the doubling effect of carbon dioxide ( ) on temperature and precipitation was modeled as the most important climatic parameters. the resulting hythergraph and ambrothermic models for tabriz indicate monthly increases of temperature and precipitat...

Linear models are widely used to perform time series forecasting. The Autoregressive stand out, due their simplicity in the parameters adjustment based on close-form solution. and Moving Average (ARMA) Infinite Impulse Response filters (IIR) also good alternatives, since they recurrent structures. However, is more complex, problem has no analytical This investigation performs linear predict mon...

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...