2006
DOI: 10.1590/s0103-97332006000500027
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Estimation of cross sections for molecule-cluster interactions by using artificial neural networks

Abstract: The cross sections of D 2 (v, j) + Ni n (T ), n = 19 and 20, collision systems have been estimated by using Artificial Neural Networks (ANNs). For training, previously determined cross section values via molecular dynamics simulation have been used. The performance of the ANNs for predicting any quantities in moleculecluster interaction has been investigated. Effects of the temperature of the clusters and the rovibrational states of the molecule are analyzed. The results are in good agreement with previous stu… Show more

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Cited by 4 publications
(4 citation statements)
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References 33 publications
(41 reference statements)
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“…[3] As a neural network can accept different input data , the use of this technology proved to be adequate for modeling field collected data , such as data monitoring water quality , hydrologic parameters for predicting disasters behavior of water body on climate change , topographic information , edaphic parameters , values of biomass , stage of crop development , simulation of the influence of environmental conditions on water quality and flow of small water bodies , soil water distribution , among others. [4]. In the paper of Sporlet [5], the researchers developed a methodology for building models of environmental fragility in neurais networks and concluded that the RNA was efficient to do this translation.…”
Section: A Neural Networkmentioning
confidence: 99%
“…[3] As a neural network can accept different input data , the use of this technology proved to be adequate for modeling field collected data , such as data monitoring water quality , hydrologic parameters for predicting disasters behavior of water body on climate change , topographic information , edaphic parameters , values of biomass , stage of crop development , simulation of the influence of environmental conditions on water quality and flow of small water bodies , soil water distribution , among others. [4]. In the paper of Sporlet [5], the researchers developed a methodology for building models of environmental fragility in neurais networks and concluded that the RNA was efficient to do this translation.…”
Section: A Neural Networkmentioning
confidence: 99%
“…The H 2 /Pt(111) and the H 2 /Cu(111) systems were chosen as examples to show the applicability of this approach. In another study related with molecular interaction with metallic surfaces Boyukata et al 21 applied NNs for the determination of the dissociative chemisorption probabilities for H 2 /Ni(111) interaction.…”
Section: Neural Network To Approach Pesmentioning
confidence: 99%
“…Nonextensive statistical mechanics [14] have successfully been applied in physics (astrophysics, astronomy, cosmology, nonlinear dynamics etc) [18,19], chemistry [3], biology [20], human sciences [21], economics [22], computer sciences [2,23,24], and others [25].…”
Section: Nonextensive Statistical Mechanicsmentioning
confidence: 99%
“…Nowadays, they are being successfully applied across a wide range of problem domains, in areas such as finance, medicine, engineering, geology and physics [1][2][3]. Indeed, anywhere that there are problems of prediction or classification, neural networks are being introduced.…”
Section: Introductionmentioning
confidence: 99%