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Article
Publication date: 7 August 2018

Jamal Ouenniche, Oscar Javier Uvalle Perez and Aziz Ettouhami

Nowadays, the field of data analytics is witnessing an unprecedented interest from a variety of stakeholders. The purpose of this paper is to contribute to the subfield of…

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Abstract

Purpose

Nowadays, the field of data analytics is witnessing an unprecedented interest from a variety of stakeholders. The purpose of this paper is to contribute to the subfield of predictive analytics by proposing a new non-parametric classifier.

Design/methodology/approach

The proposed new non-parametric classifier performs both in-sample and out-of-sample predictions, where in-sample predictions are devised with a new Evaluation Based on Distance from Average Solution (EDAS)-based classifier, and out-of-sample predictions are devised with a CBR-based classifier trained on the class predictions provided by the proposed EDAS-based classifier.

Findings

The performance of the proposed new non-parametric classification framework is tested on a data set of UK firms in predicting bankruptcy. Numerical results demonstrate an outstanding predictive performance, which is robust to the implementation decisions’ choices.

Practical implications

The exceptional predictive performance of the proposed new non-parametric classifier makes it a real contender in actual applications in areas such as finance and investment, internet security, fraud and medical diagnosis, where the accuracy of the risk-class predictions has serious consequences for the relevant stakeholders.

Originality/value

Over and above the design elements of the new integrated in-sample-out-of-sample classification framework and its non-parametric nature, it delivers an outstanding predictive performance for a bankruptcy prediction application.

Details

Management Decision, vol. 57 no. 2
Type: Research Article
ISSN: 0025-1747

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Article
Publication date: 3 January 2017

A.B. Medrano-Solís, U. León-Silva and Maria Elena Nicho

The purpose of this study was to examine the copper protection against corrosion using 3-thiophenemalonic acid (3TMA).

199

Abstract

Purpose

The purpose of this study was to examine the copper protection against corrosion using 3-thiophenemalonic acid (3TMA).

Design/methodology/approach

The heterocyclic organic molecule was tested experimentally as a corrosion inhibitor of copper in two different concentrations (0.01 M and 0.001 M) in 0.5 M solutions of sodium chloride and sulfuric acid by AC electrochemical and DC techniques.

Findings

Results showed that the organic compound was adsorbed chemically on the copper surface, and the inhibitions mechanism was both anodic and cathodic. The corrosion mechanism was under mixed control: charge transfer from metal to the environment through the double electrochemical layer, and diffusion processes.

Practical implications

This inhibitor could have application in water cooling systems.

Originality/value

The results of this paper showed that 3TMA could be used for reducing corrosion rates of copper in solutions of sodium chloride and sulfuric acid.

Details

Anti-Corrosion Methods and Materials, vol. 64 no. 1
Type: Research Article
ISSN: 0003-5599

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