Kriging, Polynomial Chaos Expansion, and Low-Rank Approximations in Material Science and Big Data Analytics
Author:
Affiliation:
1. Department of Civil, Environmental and Architectural Engineering, University of Colorado, Boulder, Colorado, USA.
2. College of Computer, Mathematical and Natural Sciences, University of Maryland, College Park, Maryland, USA.
Publisher
Mary Ann Liebert Inc
Subject
Information Systems and Management,Computer Science Applications,Information Systems
Link
https://www.liebertpub.com/doi/pdf/10.1089/big.2022.0124
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1. Statistical methods in concrete research
2. Machine learning prediction of mechanical properties of concrete: Critical review
3. Design of Experiment on Concrete Mechanical Properties Prediction: A Critical Review
4. Estimating compressive strength of modern concrete mixtures using computational intelligence: A systematic review
5. Can the compressive strength of concrete be estimated from knowledge of the mixture proportions?: New insights from statistical analysis and machine learning methods
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