in recent years, wind energy has a remarkable growth in the world, but one of the important problems of power generated from wind is its uncertainty and corresponding power. for solving this problem, some approaches have been presented. recently, the artificial neural networks (ann) as a heuristic method has more applications for this propose. in this paper, short-term (1 hour) and mid-term (24...

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...

profitability as the most important factor in decision-making, has always been considered by stake­holders in the company's profitability. also can be a basis for evaluating the performance of the managers. the ability to predict the profitability can be very useful to help decision-makers. that's why one of the most important issues is the expected profitability. the importance of th...

the quantitative structure-retention relationship (qsrr) of nanoparticles in roadside atmosphere against the comprehensive two-dimensional gas chromatography which was coupled to high-resolution time-of-flight mass spectrometry was studied. the genetic algorithm (ga) was employed to select the variables that resulted in the best-fitted models. after the variables were selected, the linear multi...

abstract background and purpose: eutrophication is one of the major environmental problems in waterways causing substantial adverse impact on domestic, livestock and recreational use of water resources. aras dam, iran which provides arasful city with drinking water, has chronic algal blooms since 1990. levels of up to 900,000 cells/ml of toxic cyanobacteria (mainly anabaena and microcystis) hav...

in this study, a model for estimating the nfs thermal conductivity by using a gmdh-pnn has been investigated. nfs thermal conductivity was modeled as a function of the nanoparticle size, temperature, nanoparticle volume fraction and the thermal conductivity of the base fluid and nanoparticles. for this purpose, the developed network contains 8 layers with 2 inputs in each layer and also trainin...

the aim of this work is to use self organizing map (som) for clustering of locomotion kinetic characteristics in normal and parkinson’s disease. the classification and analysis of the kinematic characteristics of human locomotion has been greatly increased by the use of artificial neural networks in recent years. the proposed methodology aims at overcoming the constraints of traditional analysi...

background: diabetes and hypertension are important non-communicable diseases and their prevalence is important for health authorities. the aim of this study was to determine the predictive precision of the bivariate logistic regression (lr) and artificial neutral network (ann) in concurrent diagnosis of diabetes and hypertension. methods: this cross-sectional study was performed with 12000 ira...

many efforts have been made to model the the hot deformation (dynamic recrystallization) flow curves of different materials. phenomenological constitutive models, physical-based constitutive models and artificial neural network (ann) models are the main methods used for this purpose. however, there is no report on the modeling of warm deformation (dynamic spheroidization) flow curves of any kin...