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Surface response regression and machine learning techniques to predict the characteristics of pervious concrete using non-destructive measurement: Ultrasonic pulse velocity and electrical resistivity
Research article (Measurement, 2023) · cited 54× · AI/ML
Surface response regression and machine learning techniques to predict the characteristics of pervious concrete using non-destructive measurement: Ultrasonic pulse velocity and electrical resistivity
Summary
Surface response regression and machine learning techniques to predict the characteristics of pervious concrete using non-destructive measurement: Ultrasonic pulse velocity and electrical resistivity is a scholarly article[1].
Key Facts
Surface response regression and machine learning techniques to predict the characteristics of pervious concrete using non-destructive measurement: Ultrasonic pulse velocity and electrical resistivity's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). Surface response regression and machine learning techniques to predict the characteristics of pervious concrete using non-destructive measurement: Ultrasonic pulse velocity and electrical resistivity. Retrieved May 24, 2026, from https://4ort.xyz/entity/surface-response-regression-and-machine-learning-techniques-to-predict-the-characteristics-of-pervious-concrete-using-no
MLA“Surface response regression and machine learning techniques to predict the characteristics of pervious concrete using non-destructive measurement: Ultrasonic pulse velocity and electrical resistivity.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/surface-response-regression-and-machine-learning-techniques-to-predict-the-characteristics-of-pervious-concrete-using-no.
BibTeX@misc{4ortxyz_surface-response-regression-and-machine-learning-techniques-to-predict-the-characteristics-of-pervious-concrete-using-no_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Surface response regression and machine learning techniques to predict the characteristics of pervious concrete using non-destructive measurement: Ultrasonic pulse velocity and electrical resistivity}}, year = {2026}, url = {https://4ort.xyz/entity/surface-response-regression-and-machine-learning-techniques-to-predict-the-characteristics-of-pervious-concrete-using-no}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Surface response regression and machine learning techniques to predict the characteristics of pervious concrete using non-destructive measurement: Ultrasonic pulse velocity and electrical resistivity — https://4ort.xyz/entity/surface-response-regression-and-machine-learning-techniques-to-predict-the-characteristics-of-pervious-concrete-using-no (retrieved 2026-05-24)
