An artificial neural network has been used to determine the volume flux and rejections of Ca2+ , Na+ and Cl¯, as a function of transmembrane pressure and concentrations of Ca2+, polyethyleneimine, and polyacrylic acid in water softening by nanofiltration process in presence of polyelectrolytes. The feed-forward multi-layer perceptron artificial neural network including an eight-neuron hidde...

Accurate information on Young’s modulus (E) is required for simulating rock deformation in mines; the other hand, it very cumbersome to obtain laboratory and collecting drilled cores sufficient amounts, especially case of soft rocks, quite impossible. Empirical equations were deducted E from easily determinable properties, final model was selected through different statistical strength paramete...

natural fire inflicting irreparable damage to rangelands and forest areas is cause changes in landscape ecology. the purpose of this research is comparison of artificial neural network (ann) and line regression (lr) models to predict of forest and rangelands fires to this end, the data consist fire burned area and fire were used weather data over a period of 7 years (2006-2012(.the result indic...

Artificial neural network (ANN) is a humanly constructed network which is based on the human brain neural network. BP neutral network (BPNN), as a typical forward ANN, can approximate any nonlinear continuous rational function. In this paper we use the BPNN to modify the Non-Line-of-Sight (NLOS) Time Difference of Arrival (TDOA) measurement value to make it closer to the Line-of-Sight (LOS) mea...

In this study, a method based on using image processing and artificial neural network is introduced to determine pelt color and curl size of newborn lambs in Zandi sheep. The data was collected from 300 newborn lambs reared in the Zandi sheep breeding centre of Khojir, Tehran. Primarily, curl size and pelt color of new born lambs was recorded by experienced appraisers, and at the same time, sev...

background: one issue of concern in water supply is the quality of water. measuring the qualitative parameters of water is time-consuming and costly. predicting these parameters using various models leads to a reduction in related expenses and the presentation of overall and comprehensive statistics for water resource management. methods: the present study used an artificial neural network (ann...

gas hydrates are a costly problem when they plug oil and gas pipelines. the best way to determine the hft and pressure is to measure these conditions experimentally for every gas system. since this is not practical in terms of time and money, correlations are the other alternative tools. there are a small number of correlations for specific gravity method to predict the hydrate formation. as th...

one of the main aims of water resource planners and managers is to estimate and predict the parameters of groundwater quality so that they can make managerial decisions. in this regard, there have many models developed, proposing better management in order to maintain water quality. most of these models require input parameters that are either hardly available or time-consuming and expensive to...

a neural network is developed for the determination of leaky confined aquifer parameters. leakage into the aquifer takes place from the storage in the confining aquitard. the network is trained for the well function of leaky confined aquifers by the back propagation technique and adopting the levenberg–marquardt optimization algorithm. by applying the principal component analysis (pca) on the a...