conventionally, regression and time series analyses have been employed in modeling water demand forecasts. in recent years, the relatively new technique of neural networks (nns) has been proposed as an efficient tool for modeling and forecasting. the objective of this study is to investigate the relatively new technique of gmdh – type neural networks for the use of forecasting long – term urban...

abstract to get ride of fragile and unsustainable single product export, a comprehensive knowledge of export potential and comparative advantage is required. agricultural products can be considered as a suitable target for this purpose. for more efficient planning for agricultural products export, proper forecasting is necessary. to achieve this goal, two methods were used and compared. first, ...

A parametric study was carried out in order to investigate the buckling capacity of the vertically stiffened cylindrical shells. To this end ANSYS software was used. Cylindrical steel shells with different yield stresses, diameter-to-thickness ratios (D/t) and number of stiffeners were modeled and their buckling capacities were calculated by displacement control nonlinear static analysis.  Radi...

estimation (forecasting) of industrial production costs is one of the most important factor affecting decisions in the highly competitive markets. thus, accuracy of the estimation is highly desirable. hibrid regression neural network is an approach proposed in this paper to obtain better fitness in comparison with regression analysis and the neural network methods. comparing the estimated resul...