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Use of interpretable machine learning approaches for quantificationally understanding the performance of steel fiber-reinforced recycled aggregate concrete: From the perspective of compressive strength and splitting tensile strength

Research article (Engineering Applications of Artificial Intelligence, 2024) · cited 105× · AI/ML
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Use of interpretable machine learning approaches for quantificationally understanding the performance of steel fiber-reinforced recycled aggregate concrete: From the perspective of compressive strength and splitting tensile strength

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Use of interpretable machine learning approaches for quantificationally understanding the performance of steel fiber-reinforced recycled aggregate concrete: From the perspective of compressive strength and splitting tensile strength is a scholarly article[1].

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  • Use of interpretable machine learning approaches for quantificationally understanding the performance of steel fiber-reinforced recycled aggregate concrete: From the perspective of compressive strength and splitting tensile strength's instance of is recorded as scholarly article[2].

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Wenguang Chen

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  1. [2] ↑ . wikidata.org.

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  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Use of interpretable machine learning approaches for quantificationally understanding the performance of steel fiber-reinforced recycled aggregate concrete: From the perspective of compressive strength and splitting tensile strength. Retrieved May 24, 2026, from https://4ort.xyz/entity/use-of-interpretable-machine-learning-approaches-for-quantificationally-understanding-the-performance-of-steel-fiber-rei
MLA “Use of interpretable machine learning approaches for quantificationally understanding the performance of steel fiber-reinforced recycled aggregate concrete: From the perspective of compressive strength and splitting tensile strength.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/use-of-interpretable-machine-learning-approaches-for-quantificationally-understanding-the-performance-of-steel-fiber-rei.
BibTeX @misc{4ortxyz_use-of-interpretable-machine-learning-approaches-for-quantificationally-understanding-the-performance-of-steel-fiber-rei_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Use of interpretable machine learning approaches for quantificationally understanding the performance of steel fiber-reinforced recycled aggregate concrete: From the perspective of compressive strength and splitting tensile strength}}, year = {2026}, url = {https://4ort.xyz/entity/use-of-interpretable-machine-learning-approaches-for-quantificationally-understanding-the-performance-of-steel-fiber-rei}, note = {Accessed: 2026-05-24}}
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