application of automatic systems, including discharge measurement technology is one of the effective methods for improving delivery management, water use efficiency, flexibility, and performance of irrigation networks. several aspects such as hydraulic, technical, physical, environmental, economic, social, and managerial, have significant impact on these systems selection. due to diversity of t...

abstract: despite the importance of predictive variable in prediction, in most of the research in the field of auditors’ opinion the purpose was rendering the suitable models. meanwhile, less attention was paid to the selection of optimal predictive variable and appropriate models of these selection. therefore, in most of these research the predictive variables were chosen randomly and accordin...

one of the most appropriate approaches for flood forecasting is using peak discharge data of hydrometric stations in each region. however, lack of such stations or short duration of data in most parts of the country, make it necessary to use some alternative methods in order to estimate the flood discharge properly. one of these approaches is regional flood analysis method that in a region usin...

In this paper we propose an approach to variable selection that uses a neural-network model as the tool to determine which variables are to be discarded. The method performs a backward selection by successively removing input nodes in a network trained with the complete set of variables as inputs. Input nodes are removed, along with their connections, and remaining weights are adjusted in such ...

introduction: hydrology cycle of river basins and water resources availability in arid and semi-arid regions are highly affected by climate changes, so that recently the increase of temperature due to the increase of greenhouse gases have led to anomaly in the earth’ climate system. at present, general circulation models (gcms) are the most frequently used models for projection of different cli...

Adaptive classification is an important online problem in data analysis. The nonlinear and nonstationary nature of much data makes standard static approaches unsuitable. In this paper, we propose a set of sequential dynamic classification algorithms based on extension of nonlinear variants of Bayesian Kalman processes and dynamic generalized linear models. The approaches are shown to work well ...

as a direct consequence of warmer temperatures, the hydrologic cycle will undergo significant impact with accompanying changes in the rates of precipitation and evaporation. climate change will cause changes in climate variable such as precipitation, temperature, sunshine hours, wind speed and etc. so as a result of climate variable change, the related variable such as potential evapotranspirat...