ARTIFICIAL NEURAL-NETWORK FOR IDENTIFICATION OF A SUBSTANCE FROM A MOSSBAUER DATA-BANK

被引：11

作者：

SALLES, EOT

DESOUZA, PA

GARG, VK

机构：

[1] UNIV FED ESPIRITO SANTO,DEPT FIS,BR-29060900 VITORIA,BRAZIL

[2] UNIV FED ESPIRITO SANTO,DEPT ELECT ENGN,BR-29060900 VITORIA,BRAZIL

来源：

NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION B-BEAM INTERACTIONS WITH MATERIALS AND ATOMS | 1994年 / 94卷 / 04期

关键词：

D O I：

10.1016/0168-583X(94)95427-5

中图分类号：

TH7 [仪器、仪表];

学科分类号：

0804 ; 080401 ; 081102 ;

摘要：

Mossbauer data and references of the minerals reported in the literature have been stored in a computer. Artificial neutral networks (ANN) were taught with the average values of experimental data of isomer shift quadrupole splitting of known mineral systems (sulphate, sulphide and sulphites, and silicates). Artificial neural networks successfully identified the unknown substance when fed with the new values of isomer shift and quadrupole splitting.

引用

页码：499 / 502

页数：4

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