Feature Selection and Neural Network for analysis of microstructural changes in magnetic materials

J. A. Pérez-Benitez; L. R. Padovese

doi:10.1016/j.eswa.2011.02.088

Feature Selection and Neural Network for analysis of microstructural changes in magnetic materials

J. A. Pérez-Benitez, L. R. Padovese

Research output: Contribution to journal › Article › peer-review

23 Scopus citations

Abstract

This work presents a Feature Selection Algorithm for optimization of a Probabilistic Neural Network. The aim of this Probabilistic Neural Network is classifying signals obtained from magnetic material samples where two micro-structural parameters were changed simultaneously. The combination of the Feature Selection Algorithm with the Probabilistic Neural Network shows both, classification rate outcomes and classification speed, higher than those coming from traditional Probabilistic Neural Networks.

Original language	English
Pages (from-to)	10547-10553
Number of pages	7
Journal	Expert Systems with Applications
Volume	38
Issue number	8
DOIs	https://doi.org/10.1016/j.eswa.2011.02.088
State	Published - Aug 2011
Externally published	Yes

Keywords

Envelope
Feature selection
Neural Networks
Nondestructive methods
Probabilistic Neural Networks

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10.1016/j.eswa.2011.02.088

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abstract = "This work presents a Feature Selection Algorithm for optimization of a Probabilistic Neural Network. The aim of this Probabilistic Neural Network is classifying signals obtained from magnetic material samples where two micro-structural parameters were changed simultaneously. The combination of the Feature Selection Algorithm with the Probabilistic Neural Network shows both, classification rate outcomes and classification speed, higher than those coming from traditional Probabilistic Neural Networks.",

keywords = "Envelope, Feature selection, Neural Networks, Nondestructive methods, Probabilistic Neural Networks",

author = "P{\'e}rez-Benitez, {J. A.} and Padovese, {L. R.}",

note = "Funding Information: The authors would like to thank the financial support of Brazilian agency FAPESP/ Proc. No. 2008/10859-0.",

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AU - Padovese, L. R.

N1 - Funding Information: The authors would like to thank the financial support of Brazilian agency FAPESP/ Proc. No. 2008/10859-0.

PY - 2011/8

Y1 - 2011/8

N2 - This work presents a Feature Selection Algorithm for optimization of a Probabilistic Neural Network. The aim of this Probabilistic Neural Network is classifying signals obtained from magnetic material samples where two micro-structural parameters were changed simultaneously. The combination of the Feature Selection Algorithm with the Probabilistic Neural Network shows both, classification rate outcomes and classification speed, higher than those coming from traditional Probabilistic Neural Networks.

AB - This work presents a Feature Selection Algorithm for optimization of a Probabilistic Neural Network. The aim of this Probabilistic Neural Network is classifying signals obtained from magnetic material samples where two micro-structural parameters were changed simultaneously. The combination of the Feature Selection Algorithm with the Probabilistic Neural Network shows both, classification rate outcomes and classification speed, higher than those coming from traditional Probabilistic Neural Networks.

KW - Envelope

KW - Feature selection

KW - Neural Networks

KW - Nondestructive methods

KW - Probabilistic Neural Networks

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DO - 10.1016/j.eswa.2011.02.088

M3 - Artículo

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SP - 10547

EP - 10553

JO - Expert Systems with Applications

JF - Expert Systems with Applications

IS - 8

ER -

Feature Selection and Neural Network for analysis of microstructural changes in magnetic materials

Abstract

Keywords

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