Prediction of Zarrinehrud River Run-Off in the Climate Change Condition using Artificial Neural Networks

Prediction of Gas Lift Parameters Using Artificial Neural Networks

To Investigate Of Change in Waves Height under the influence of climate change using Artificial neural network and wavelet

Prediction of the waves’ specifications that is one of the key factors effective on transformation ofcoasts, production of renewable energies and design of marine structures, has always been importante.Height of the waves is one of the most important and effective parameters of the wave. Differentfactors are effective in variation of the waves’ height. In this research, variation in waves heigh...

Prediction of the deformation modulus of rock masses using Artificial Neural Networks and Regression methods

Static deformation modulus is recognized as one of the most important parameters governing the behavior of rock masses. Predictive models for the mechanical properties of rock masses have been used in rock engineering because direct measurement of the properties is difficult due to time and cost constraints. In this method the deformation modulus is estimated indirectly from classification syst...

The Prediction of Surface Tension of Ternary Mixtures at Different Temperatures Using Artificial Neural Networks

In this work, artificial neural network (ANN) has been employed to propose a practical model for predicting the surface tension of multi-component mixtures. In order to develop a reliable model based on the ANN, a comprehensive experimental data set including 15 ternary liquid mixtures at different temperatures was employed. These systems consist of 777 data points generally containing hydrocar...

Prediction the Return Fluctuations with Artificial Neural Networks' Approach

Time changes of return, inefficiency studies performed and presence of effective factors on share return rate are caused development modern and intelligent methods in estimation and evaluation of share return in stock companies. Aim of this research is prediction of return using financial variables with artificial neural network approach. Therefore, the statistical population of this study incl...

Prediction of the Surface Run off in Semirom Mehregerd Watershed Using ARIMA Model

By understanding the temporal and spatial variations of water resources in a region, the better management and planning of water resources and water consumptions can be done. Time series modeling, if used correctly, will lead to acceptable results in this regard. For this purpose, the monthly runoff time series for 28 years was prepared at the hydrometric stations of Mehregerd region and the pr...