Reply to comment on ‘Composition-based aluminum alloy selection using an artificial neural network’

Jaka Fajar Fatriansyah; Raihan Kenji Rizqillah; Iping Suhariadi; Andreas Federico; Ade Kurniawan

doi:10.1088/1361-651X/ad4574

Reply to comment on ‘Composition-based aluminum alloy selection using an artificial neural network’

Jaka Fajar Fatriansyah, Raihan Kenji Rizqillah, Iping Suhariadi, Andreas Federico, Ade Kurniawan

Department of Metallurgical and Material Engineering

Research output: Contribution to journal › Comment/debate

Abstract

This reply is addressed to comments on our paper entitled ‘Composition-based Aluminum Alloy Selection Using an Artificial Neural Network.’ There are six main comments, and we addressed the comments carefully. This machine learning (ML) modeling is only part of the development of a broader material selection (or material screening) system. Consideration of other material properties can certainly be included through the integration of ML systems.

Original language	English
Article number	058002
Journal	Modelling and Simulation in Materials Science and Engineering
Volume	32
Issue number	5
DOIs	https://doi.org/10.1088/1361-651X/ad4574
Publication status	Published - Jul 2024

Keywords

aluminum alloy
artificial neural network
fatigue life
inverse design
machine learning

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10.1088/1361-651X/ad4574

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title = "Reply to comment on {\textquoteleft}Composition-based aluminum alloy selection using an artificial neural network{\textquoteright}",

abstract = "This reply is addressed to comments on our paper entitled {\textquoteleft}Composition-based Aluminum Alloy Selection Using an Artificial Neural Network.{\textquoteright} There are six main comments, and we addressed the comments carefully. This machine learning (ML) modeling is only part of the development of a broader material selection (or material screening) system. Consideration of other material properties can certainly be included through the integration of ML systems.",

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AU - Suhariadi, Iping

AU - Federico, Andreas

AU - Kurniawan, Ade

PY - 2024/7

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N2 - This reply is addressed to comments on our paper entitled ‘Composition-based Aluminum Alloy Selection Using an Artificial Neural Network.’ There are six main comments, and we addressed the comments carefully. This machine learning (ML) modeling is only part of the development of a broader material selection (or material screening) system. Consideration of other material properties can certainly be included through the integration of ML systems.

AB - This reply is addressed to comments on our paper entitled ‘Composition-based Aluminum Alloy Selection Using an Artificial Neural Network.’ There are six main comments, and we addressed the comments carefully. This machine learning (ML) modeling is only part of the development of a broader material selection (or material screening) system. Consideration of other material properties can certainly be included through the integration of ML systems.

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KW - artificial neural network

KW - fatigue life

KW - inverse design

KW - machine learning

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Reply to comment on ‘Composition-based aluminum alloy selection using an artificial neural network’

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