In this paper an application of ANN models are presented to estimate the roughness of a given finishing operation. The approach uses the acoustic emission sensor as an information source to improve the estimation capability of the ANN model. Building up the ANN model to avoid the problem of overlapping and noninvertable dependencies used a new approach. The model was built up and the roughness ...

Abstract: In order to predict hot deformation behavior of superalloy nimonic 80A, a back-propagational artificial neural network (BP-ANN) and strain-dependent Arrhenius-type model were established based on the experimental data from isothermal compression tests on a Gleeble-3500 thermo-mechanical simulator at temperatures ranging of 1050–1250 ̋C, strain rates ranging of 0.01–10.0 s ́1. A comparis...

prediction of the heavy metals in the groundwater is important in developing any appropriate remediation strategy. this paper attempts to predict heavy metals (pb, zn and cu) in the groundwater from arak city, using artificial neural network (ann) algorithm by taking major elements (hco3, so4) in the groundwater from arak city. for this purpose, contamination sources in the groundwater were rec...

in recent years, artificial neural networks (anns) have been widely used for flood esti-mation. in this study, an ann model based on the geomorphologic characteristics of a watershed such as the number of possible paths and their probabilities is developed (gann model). nodes in the input layer are allocated to the surface flows, subsurface flows, excess-rainfall and infiltrated rain. the numbe...

background treatment with peginterferon alpha-2b plus ribavirin is the current standard therapy for chronic hepatitis c (chc). however, many host related and viral parameters are associated with different outcomes of combination therapy. objectives the aim of this study was to develop an artificial neural network (ann) model to predetermine individual responses to therapy based on patient’s dem...

prediction of precipitation is very important. regarding to the non- linear relationships and uncertainty of models, there is no superior and persuasive model among various proposed models to simulate precise precipitation and its amount. wavelet is one of the novel and very effective methods in time series and signals analyzing, that has been considered in the field of hydrology in recent year...

runoff estimation is one of the main challenges encountered in water and watershed management. spatial and temporal changes of factors which influence runoff due to het-erogeneity of the basins explain the complicacy of relations. artificial neural network (ann) is one of the intelligence techniques which is flexible and doesn’t call for any much physically complex processes. these networks can...

in this work, quantitative structure-property relationship (qspr) approaches were used to predict the redox potential of 42 phenolic antioxidants. the structures of all compounds optimized by the am1 semi-empirical method and then a large number of molecular descriptors were calculated for each compound in the data set. subsequently, stepwise multilinear regression was applied to select the mos...