estimating the saturated hydraulic conductivity of granular material, using artificial neural network, based on grain size distribution curve

Estimating the Saturated Hydraulic Conductivity of Granular Material, Using Artificial Neural Network, Based on Grain Size Distribution Curve

Nanofluid Thermal Conductivity Prediction Model Based on Artificial Neural Network

Heat transfer fluids have inherently low thermal conductivity that greatly limits the heat exchange efficiency. While the effectiveness of extending surfaces and redesigning heat exchange equipments to increase the heat transfer rate has reached a limit, many research activities have been carried out attempting to improve the thermal transport properties of the fluids by adding more thermally c...

scour modeling piles of kambuzia industrial city bridge using hec-ras and artificial neural network

today, scouring is one of the important topics in the river and coastal engineering so that the most destruction in the bridges is occurred due to this phenomenon. whereas the bridges are assumed as the most important connecting structures in the communications roads in the country and their importance is doubled while floodwater, thus exact design and maintenance thereof is very crucial. f...

Forecasting of Covid-19 cases based on prediction using artificial neural network curve fitting technique

Artificial neural network is considered one of the most efficient methods in processing huge data sets that can be analyzed computationally to reveal patterns, trends, prediction, forecasting etc. It has a great prospective in engineering as well as in medical applications. The present work employs artificial neural network-based curve fitting techniques in prediction and forecasting of the Cov...

Arti fi cial Neural Network Estimation of Saturated Hydraulic Conductivity

cial neural networks have become a common tool for modeling complex “input–output” dependencies. In the past, neural network models have been used as a special class of pedotransfer functions (PTFs) using feed-forward back propagation or radial basis functions to approximate any continuous (nonlinear) function (Hecht-Nielsen, 1990; Pachepsky et al., 1996; Schaap and Bouten, 1996; Minasny and Mc...

using fractal dimension of particle size in estimating saturated hydraulic conductivity

one of the important aspects of soil is, knowing the relationships between spatial features of soil and quantity in statistical model. the goal of this research is to estimate saturated hydraulic conductivity by regression and co-active neuro-fuzzy inference system (anfis) with using the parameters of bulk density, real density, porosity, fractal dimension of particle size, and clay percent, si...