A Fatigue Strength Predictor for Steels Using Ensemble Data Mining-Reference-Cited by-同舟云学术

A Fatigue Strength Predictor for Steels Using Ensemble Data Mining

Published:2016-10-24 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 25th ACM International on Conference on Information and Knowledge Management
language:
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Author:

Agrawal Ankit¹,Choudhary Alok¹

Affiliation:

1. Northwestern University, Evanston, IL, USA

Funder

National Institute of Standards and Technology

Air Force Office of Scientific Research

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/2983323.2983343

Reference7 articles.

1. Materials Genome Initiative for Global Competitiveness June 2011; OSTP 2011. Materials Genome Initiative for Global Competitiveness June 2011; OSTP 2011.

2. Perspective: Materials informatics and big data: Realization of the "fourth paradigm" of science in materials science;Agrawal A.;APL Materials,2016

3. Exploration of data science techniques to predict fatigue strength of steel from composition and processing parameters;Agrawal A.;Integrating Materials and Manufacturing Innovation,2014

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