Hydraulic jumps have immense practical utility in hydraulic engineering and allied fields, such as energy dissipater to dissipate the excess energy of flowing water downstream of hydraulic structures (spillways and sluice gates), efficient operation of flow measurement flumes, chlorinating of wastewater, aeration of streams which are polluted by biodegradable wastes and many other cases. The le...

Background and aims: Since accurate forecasts help inform decisions for preventive health-careintervention and epidemic control, this goal can only be achieved by making use of appropriatetechniques and methodologies. As much as forecast precision is important, methods and modelselection procedures are critical to forecast precision. This study aimed at providing an overview o...

Evaporation from soil columns in the presence of a water table is a long lasting subject that has received great attention for many decades. Available analytical studies on the subject often involve an assumption that the potential evaporation rate is much less than the saturated hydraulic conductivity of the soil. In this study, we develop a new semi-analytical method to estimate the evaporati...

The paper deals with Data Envelopment Analysis (DEA) and Artificial Neural Network (ANN). We believe that solving for the DEA efficiency measure, simultaneously with neural network model, provides a promising rich approach to optimal solution. In this paper, a new neural network model is used to estimate the inefficiency of DMUs in large datasets.

Leakage rates are evaluated for a landfill barrier system having a compacted clay liner (CCL) underlain by a vadose zone of variable thickness. A numerical unsaturated flow model SEEP/W is used to simulate the moisture flow regime and steady-state leakage rates for the cases of unsaturated zones with different soil types and thicknesses. The results of the simulations demonstrate that harmonic ...

This study was conducted to investigate the prediction of growth performance using linear regression and artificial neural network (ANN) in broiler chicken. Artificial neural networks (ANNs) are powerful tools for modeling systems in a wide range of applications. The ANN model with a back propagation algorithm successfully learned the relationship between the inputs of metabolizable energy (kca...