Net all-wave surface radiation (Rn) is one of the most important fundamental parameters in various applications. However, conventional Rn measurements are difficult to collect because of the high cost and ongoing maintenance of recording instruments. Therefore, various empirical Rn estimation models have been developed. This study presents the results of two artificial neural network (ANN) mode...

in this paper an intelligent method through general regression neural networks (grnn) is presented to estimate the depth of salt domes from gravity data. neural networks are as a good tool for automatic interpretation of geophysical data especially for depth estimation of gravity anomalies. the gravity signal is a nonlinear function of depth and density and the geometrical parameters of the bur...

Path loss modeling is a crucial consideration in radio engineering for wireless networks. Over the years, diverse techniques have been implemented attempts to accurately predict path across given terrain. In this study, predictors created on bases of artificial neural networks (ANN) were used estimate rural section Nigerian middle-belt grassland. The ANN structures considered Generalized Regres...

The use of Artificial Intelligence methods is becoming increasingly common in the modeling and forecasting of hydrological and water resource processes. In this study, applicability of Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) methods, Generalized Regression Neural Networks (GRNN) and Feed 5 Forward Neural Networks (FFNN), for forecasting of daily river f...

The quantification of diurnal and seasonal gas (NH3, H2S, and CO2) and PM10 concentrations and emission rates (GPCER) from livestock production facilities is indispensable for the development of science-based setback determination methods and evaluation of improved downwind community air quality resulting from the implementation of gas pollution control. The purpose of this study was to employ ...

Neural networks provide the opportunity to estimate specific components of engineering problems. They are decomposed complex problems into different parts. Thus, it can be easy compete with each them through neural networks. In this paper, was purposed average speed a 6-line road’s cross-section by observed traffic variables, such as numbers vehicles and occupancy values, using radial basis fun...