in this research, a two-phase algorithm based on the artificial neural network (ann) and a harmony search (hs) algorithm has been developed with the aim of assessing the reliability of structures with implicit limit state functions. the proposed method involves the generation of datasets to be used specifically for training by finite element analysis, to establish an ann model using a proven an...

Artificial neural networks (ANNs) as a powerful approach have been widely utilized to demonstrate some of the engineering problems. A three-layer ANN including three neurons in the hidden layer is considered to produce a verified pattern for assessing the compressive strength of concrete incorporating metakaolin (MK). For this purpose, an extensive database including 469 experimental specimens ...

[1] Runoff generation in Alpine regions is typically affected by snow processes. Snow accumulation, storage, redistribution, and ablation control the availability of water. In this study, several robust parameterizations describing snow processes in Alpine environments were implemented in a fully distributed, physically based hydrological model. Snow cover development is simulated using differe...

introduction: with using multiple linear regression (mlr), can simultaneously analyses several different variables, but to get the desirable results from the mlr, the samples must be much and accurate. therefore, this method has high sensitivity and may cause errors in results. in addition, to use this method, the variable must have normal distribution and modification follow from a linear rela...

background: as bremsstrahlung photon beam fluence is important parameter to be known in a photonuclear reaction experiment as the number of produced particle is strongly depends on photon fluence. materials and methods: photon production yield from different thickness of aluminum target has been estimated using artificial neural network (ann) model. target thickness and incoming electron energy...

This paper presents an alternative approach to time series forecasting, through use of artificial neural networks (ANNs), a relatively new concept in hydrological research. Box and Jenkins ARMAX (autoregressive moving average with exogenous inputs) models have been widely used in modeling various time series with satisfactory results. This study shows that ANNs can produce comparable, to ARMAX,...

 Background: Although experiments on water quality are time consuming and expensive, models are often employed as supplement to simulate water quality. Artificial neural network (ANN) is an efficient tool in hydrologic studies, yet it cannot predetermine its results in the forms of maps and geo-referenced data. Methods: In this study, ANN was applied to simulate groundwater quality ...

in this work quantitative structure activity relationship (qsar) methodology was applied for modeling and prediction of cellular response to polymers that have been designed for tissue engineering. after calculation and screening of molecular descriptors, linear and nonlinear models were developed by using multiple linear regressions (mlr) and artificial neural network (ann) methods. the root m...

A great deal of work has been done in the area of off-line signature verification over the last two decades. Offline systems are of interest in scenarios where only hard copies of signatures are available, especially where a large number of documents need to be authenticated. This paper is inspired by, amongst other things, the potential financial benefits that the automatic clearing of cheques...

large impervious surfaces and man-made waterways are the characteristic of urban area. increasing urbanization and rapid growth of cities in recent decades towards the upstream watershed, has been severely affected on rainfall-runoff processes in urban area. therefore, to computer models in order to illustrate these processes the proper design or assessment of urban drainage systems has special...