kashan aquifer is adjacent to salt lake. because of this adjacency, the saline water of the lake has moved to the aquifer. in this study groundwater quality of the aquifer was simulated using artificial neural network (ann) model. for this purpose, the dominant ion of water was first determined by piper diagram. results showed that the sodium chloride is the dominant ion of water and so it was ...

Most Artificial neural networks (ANN) models used in the remote sensing classification are based on the multilayer perceptron (MLP) with back-propagation (BP) training algorithm. Compared to conventional statistical classifiers, MLP classifiers are non-parametric and distribution-free and is thus less restrictive in approximation, especially when distributions of features are strongly non-Gauss...

Ecosystem of arid and semiarid regions of the world, much of the country lies in the sensitive and fragile environment Canvases are that factors in the extinction and destruction are easily destroyed in this paper, artificial neural networks (ANNs) are introduced to obtain improved regional low-flow estimates at ungauged sites. A multilayer perceptron (MLP) network is used to identify the funct...

ecosystem of arid and semiarid regions of the world, much of the country lies in the sensitive and fragile environment canvases are that factors in the extinction and destruction are easily destroyed in this paper, artificial neural networks (anns) are introduced to obtain improved regional low-flow estimates at ungauged sites. a multilayer perceptron (mlp) network is used to identify the funct...

A comparison of corporate failure models in Australia: Hybrid neural networks, logit models and discriminant analysis. A comparison of corporate failure models in Australia: Hybrid neural networks, logit models and discriminant analysis. Abstract This study investigated whether two artificial neural networks (ANNs), multilayer perceptron (MLP) and hybrid networks using statistical and ANN appro...

Artificial neural network based equalizers can be used for equalization in coherent optical OFDM systems. The artificial neural network based multilayer layer perceptron is a feed-forward network consists of one hidden layer with one or more hidden nodes between its input and output layers and can be trained by using back propagation algorithm. However, this algorithm suffers from slow converge...

This study presents a new procedure based on Artificial Neural Network (ANN) for identification of double cracks in Functionally Graded Beams (FGBs). A cantilever beam is modeled using Finite Element Method (FEM) for analyzing a double-cracked FGB and evaluation of its first four natural frequencies for different cracks depths and locations. The obtained FEM results are verified against availab...

the objective of this paper is to develop an artificial neural network (ann) model which can beused to predict temperature rise due to climate change in regional scale. in the present work data recorded overyears 1985-2008 have been used at training and testing steps for ann model. the multilayer perceptron(mlp) network architecture is used for this purpose. three applied optimization methods a...

In this study, artificial neural network was used to predict the microhardness of Al2024-multiwall carbon nanotube(MWCNT) composite prepared by mechanical alloying. Accordingly, the operational condition, i.e., the amount of reinforcement, ball to powder weight ratio, compaction pressure, milling time, time and temperature of sintering as well as vial speed were selected as independent input an...

Dynamic neural network (DNN) models provide an excellent means for forecasting and prediction of nonstationary time series. A neural network architecture, known as locally recurrent neural network ((LRNN) [71], is preferred to the traditional multilayer perceptron (MLP) because the time varying nature of a stock time series can be better represented using LRNN. The use of LRNN has demonstrated ...