This paper presents a straight forward application of Layer Recurrent Neural Network (LRNN) to predict the load of a large distribution network. Short term load forecasting provides important information about the system’s load pattern, which is a premier requirement in planning periodical operations and facility expansion. Approximation of data patterns for forecasting is not an easy task to p...

Structural breaks and existence of outliers in time series variables results in misleading forecasts. We forecast wheat and rice prices by capturing the exogenous breaks and outliers using Automatic modeling. The procedure identifies the outliers as the observations with large residuals. The suggested model is compared on the basis of Root Mean Square Error (RMSE) and Mean Absolute Percentage E...

abstract assessing moisture in the soil under cultivation of crops to achieve high performance and reduced water are necessary. knowledge of the moisture distribution in the root zone, time consuming and costly field tests that simulation models, a suitable alternative in answer to issues of movement and are water distribution. in this study assessment of soil moisture, to aid swap simulation m...

with regard to the importance of instantaneous peak discharge estimation for watershed management study, and due to the lack of and unqualified climatic and hydrologic data for estimation and measurement in countries such as iran, researchers were obliged to establish a link between constant parameters (geomorphologic) and variables (hydrologic) to present models with minimum dependence on clim...

this research develops an allometric model for estimation of biomass based on the height and dbh of trees in the hyrcanian forests of iran. an accurate allometric model reduces the uncertainty of allometric equation in biomass estimation using radar images. in this study, 317 trees were selected randomly from the 4 different dominant tree species for the development of an allometric model cover...

large-scale climatic signals including ocean-atmosphere interactions, are the main factors influencing the earth’s climatic oscillations and are the most important indices in predicting of climate variables. in this research, precipitation in the next month was predicted by applying artificial neural network (ann), neuro-fuzzy network (nfn), and multiple linear regression (mlr) in semnan synopt...

using crop simulation models is an efficient complement to experimental research. crop models can also be helpful with respect to decision-making in sustainable farming system. this study was done to estimate genetic coefficients and evaluate performanced dssat in prediction of development, growth and yield in wheat. data from various field experiments for four wheat cultivars koohdasht, shirou...