Covadonga Palencia Coto-rekin lankidetzan egindako argitalpenak (10)
2024
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Design of Mixtures and Manufacture of Self-Compacting Concretes with Recycled Aggregates (Eco-Concretes): Prediction of Compressive Strength Using Machine Learning Models
Lecture Notes in Mechanical Engineering
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To determine the compressive strength of self-compacting recycled aggregate concrete using artificial neural network (ANN)
Ain Shams Engineering Journal, Vol. 15, Núm. 2
2022
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A Comparison of Machine Learning Tools that Model the Splitting Tensile Strength of Self-Compacting Recycled Aggregate Concrete
Materials, Vol. 15, Núm. 12
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A Study on the Prediction of Compressive Strength of Self-Compacting Recycled Aggregate Concrete Utilizing Novel Computational Approaches
Materials, Vol. 15, Núm. 15
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Impact of sulfate activation of rice husk ash on the performance of high strength steel fiber reinforced recycled aggregate concrete
Journal of Building Engineering, Vol. 54
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Prediction of Splitting Tensile Strength of Self-Compacting Recycled Aggregate Concrete Using Novel Deep Learning Methods
Mathematics, Vol. 10, Núm. 13
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Satisfaction Level of Engineering Students in Face-to-Face and Online Modalities under COVID-19—Case: School of Engineering of the University of León, Spain
Sustainability, Vol. 14, Núm. 10, pp. 6269
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To determine the performance of metakaolin-based fiber-reinforced geopolymer concrete with recycled aggregates
Archives of Civil and Mechanical Engineering, Vol. 22, Núm. 3
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To predict the compressive strength of self compacting concrete with recycled aggregates utilizing ensemble machine learning models
Case Studies in Construction Materials, Vol. 16, pp. e01046