in this study, several artificial neural networks (anns) were developed to estimate seed and grain corn yields in parsabad moghan, iran. the data was collected by a face-to-face interview method from 144 corn farms during 2011. the energy ratios for seed and grain corns were calculated as 0.89 and 2.65, respectively. several multilayer perceptron anns with six neurons in the input layer and one...

awareness of the level of river flow and its fluctuations at different times is one of the significant factor to achieve sustainable development for water resource issues. therefore, the present study two hybrid models, wavelet- adaptive neural fuzzy interference system (wanfis) and wavelet- artificial neural network (wann) are used for flow prediction of gamasyab river (nahavand, hamedan, iran...

creep compliance is one of the fundamental tests of mechanistic- empirical flexible pavement design procedure in the aashto 2002 design guide. in this research, a new artificial neural network model for estimating the hma creep compliance with the generalization ability of r=0.949 has been developed successfully using feed forward multi layer perceptron artificial neural networks (anns) with le...

accurate prediction of river flow is one of the most important factors in surface water recourses management especially during floods and drought periods. in fact deriving a proper method for flow forecasting is an important challenge in water resources management and engineering. although, during recent decades, some black box models based on artificial neural networks (ann), have been develop...

forecasting of temperature is a very important in meteorology. air temperature prediction is of a concern in environment, industry and agriculture. temperature with precipitation are important factors in meteorology and are used in classification of climate. in this paper we want to predict average monthly temperature for chosen station of isfahan province. an artificial neural network is a pow...