Towards white box modeling of compressive strength of sustainable ternary cement concrete using explainable artificial intelligence (XAI)
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Title
Towards white box modeling of compressive strength of sustainable ternary cement concrete using explainable artificial intelligence (XAI)
Authors
Keywords
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Journal
APPLIED SOFT COMPUTING
Volume -, Issue -, Pages 110997
Publisher
Elsevier BV
Online
2023-11-03
DOI
10.1016/j.asoc.2023.110997
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Note: Only part of the references are listed.- A Systematic Review of Explainable Artificial Intelligence in Terms of Different Application Domains and Tasks
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- Efficient computation of counterfactual explanations and counterfactual metrics of prototype-based classifiers
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- Explainable artificial intelligence: an analytical review
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