Compressive Strength Prediction Of Recycled Concrete Based

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Compressive strength prediction of recycled concrete based ...

30/06/2018  The compressive strength of recycled concrete is closely related to these factors such as sand rate, water-cement ratio, aggregate grade, aggregate type and substitution rate, mineral fine admixture variety and dosage,.

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Prediction of the Compressive Strength of Recycled ...

Recycled aggregate concrete (RAC), due to its high porosity and the residual cement and mortar on its surface, exhibits weaker strength than common concrete. To guarantee the safe use of RAC, a compressive strength prediction model based on artificial neural

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Compressive strength prediction of recycled concrete based ...

Considering on the current difficulties of predicting the compressive strength of recycled aggregate concrete, this paper proposes a prediction model based on deep learning theory. First, the deep features of water-cement ratio, recycled coarse aggregate replacement ratio, recycled fine aggregate replacement ratio, fly ash replacement ratio as well as their combinations are learned through a ...

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Compressive strength prediction of recycled concrete based ...

The compressive strength of recycled concrete is closely related to these factors such as sand rate, water- cement ratio, aggregate grade, aggregate type and substitution rate, mineral fine admixture variety and dosage [7,8].

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Compressive strength prediction of recycled concrete based ...

Based on the results, the recycled concrete and recycled fiber concrete with the proposed mix design have a high compressive strength, and due to relatively high porosity of the recycled aggregate ...

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Prediction of the Compressive Strength of Recycled ...

To better detect the compressive strength of concrete, some scholars have studied prediction models for concrete compressive strength [21,22]. The basic properties of RAC must be verified by practical experiments, because concrete performance can be greatly affected by the composite material types and the amount of use. However, lab experiments usually require a great amount of manpower ...

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Compressive strength prediction of recycled concrete based ...

Compressive strength prediction of recycled concrete based on deep learning Fangming Denga, Yigang Hed,⇑, Shuangxi Zhoub,⇑, Yun Yuc, Haigen Chengb, Xiang Wua a School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, China bSchool of Civil Engineering and Architecture, East China Jiaotong University, Nanchang 330013, China

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Compressive strength prediction of recycled concrete based ...

Based on the results, the recycled concrete and recycled fiber concrete with the proposed mix design have a high compressive strength, and due to relatively high porosity of the recycled aggregate ...

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Prediction of the Compressive Strength of Recycled ...

Recycled aggregate concrete (RAC), due to its high porosity and the residual cement and mortar on its surface, exhibits weaker strength than common concrete. To guarantee the safe use of RAC, a compressive strength prediction model based on artificial neural network (ANN) was built in this paper, which can be applied to predict the RAC compressive strength for 28 days. A data set

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Prediction of the Compressive Strength of Recycled ...

The research area is Prediction of the compressive strength of Recycled Aggregate Concrete based on Artificial Neural Network. The manuscript has the usual structure, but part of the discussion must be separate. Some information and conclusions are known, in particular the use of ANN for the prediction of compressive strength. The presentation of new knowledge itself and the conclusion must be ...

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Compressive strength prediction of recycled concrete based ...

Abstract Considering on the current difficulties of predicting the compressive strength of recycled aggregate concrete, this paper proposes a prediction model based on deep learning theory. First, the deep features of water-cement ratio, recycled coarse aggregate replacement ratio, recycled fine aggregate replacement ratio, fly ash replacement ratio as well as their combinations are learned ...

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Prediction of the Compressive Strength of Recycled ...

Recycled aggregate concrete (RAC), due to its high porosity and the residual cement and mortar on its surface, exhibits weaker strength than common concrete. To guarantee the safe use of RAC, a compressive strength prediction model based on artificial neural network (ANN) was built in this paper, which can be applied to predict the RAC compressive strength for 28 days.

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Compressive strength prediction of recycled concrete based ...

Compressive strength prediction of recycled concrete based on deep learning @article{Deng2018CompressiveSP, title={Compressive strength prediction of recycled concrete based on deep learning}, author={Fangming Deng and Y. He and S. Zhou and Y. Yu and Haigen Cheng and Xiang Wu}, journal={Construction and Building Materials}, year={2018}, volume ...

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Compressive strength prediction of recycled concrete based ...

Considering on the current difficulties of predicting the compressive strength of recycled aggregate concrete, this paper proposes a prediction model based on deep learning theory. First, the deep features of water-cement ratio, recycled coarse aggregate replacement ratio, recycled fine aggregate replacement ratio, fly ash replacement ratio as well as their combinations are learned through a ...

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Prediction of compressive strength of recycled aggregate ...

11/04/2021  Compressive strength prediction of recycled concrete based on deep learning. Constr. Build. Mater., 175 (2018), pp. 562-569. Article Download PDF View Record in Scopus Google Scholar. S. Arora, B. Singh, B. Bhardwaj. Strength performance of recycled aggregate concrete containing mineral admixtures and their performance prediction through various modeling techniques. J. Build. Eng., 24

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Predicting Compressive Strength of Recycled Concrete for ...

Predicting Compressive Strength of Recycled Concrete for Construction 3D Printing Based on ... the prediction performance of the recycled 3D printing concrete based on neural network method can be determined. In general, the main factors affecting the performance of neural network are the number of neurons and layers in the hidden layer. Therefore, in same training function, the influence of ...

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Compressive strength prediction of recycled concrete based ...

Compressive strength prediction of recycled concrete based on deep learning Fangming Denga, Yigang Hed,⇑, Shuangxi Zhoub,⇑, Yun Yuc, Haigen Chengb, Xiang Wua a School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, China bSchool of Civil Engineering and Architecture, East China Jiaotong University, Nanchang 330013, China

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Compressive strength prediction of recycled concrete based ...

Based on the results, the recycled concrete and recycled fiber concrete with the proposed mix design have a high compressive strength, and due to relatively high porosity of the recycled aggregate ...

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Compressive strength prediction of recycled concrete based ...

Abstract Considering on the current difficulties of predicting the compressive strength of recycled aggregate concrete, this paper proposes a prediction model based on deep learning theory. First, the deep features of water-cement ratio, recycled coarse aggregate replacement ratio, recycled fine aggregate replacement ratio, fly ash replacement ratio as well as their combinations are learned ...

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Compressive strength prediction of recycled concrete based ...

Compressive strength prediction of recycled concrete based on deep learning @article{Deng2018CompressiveSP, title={Compressive strength prediction of recycled concrete based on deep learning}, author={Fangming Deng and Y. He and S. Zhou and Y. Yu and Haigen Cheng and Xiang Wu}, journal={Construction and Building Materials}, year={2018}, volume ...

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Compressive strength prediction of recycled concrete based ...

Considering on the current difficulties of predicting the compressive strength of recycled aggregate concrete, this paper proposes a prediction model based on deep learning theory. First, the deep features of water-cement ratio, recycled coarse aggregate replacement ratio, recycled fine aggregate replacement ratio, fly ash replacement ratio as well as their combinations are learned through a ...

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Predicting Compressive Strength of Recycled Concrete for ...

Predicting Compressive Strength of Recycled Concrete for Construction 3D Printing Based on Statistical Analysis of Various Neural Networks Kang Tan Department of Civil Engineering, Dalian University of Technology, Dalian, China Abstract Construction 3D printing is construction industry, but for its ichanging m-maturity, there are still many problems to be solved. One of the major prob-lems is ...

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Compressive Strength Prediction via Gene Expression ...

The data used in this study to forecast the compressive strength of recycled coarse aggregate-based concrete were taken from previously published literature and can be seen in Appendix A. A total of nine parameters including water, cement, sand, natural coarse aggregate, recycled coarse aggregate (RCA), superplasticizers, size of RCA, the density of RCA, and water absorption of RCA were taken ...

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Compressive strength Prediction recycled aggregate ...

Compressive strength Prediction recycled aggregate incorporated concrete using Adaptive Neuro-Fuzzy System and Multiple Linear Regression Funso Faladea.*, Taim Iqbala a Department of Civil Engineering, University of Lagos, Nigeria. *Corresponding Author [email protected] (Funso Falade) System (ANFIS), and Multiple Linear Regression (MLR) were Received : 19-03-2019 Accepted : 07

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Estimating the Compressive Strength of Cement-Based ...

07/08/2021  (3) Based on the prediction results from the developed model, the SVM, DT, and RF models can be used to predict the compressive strength of cement-based materials using solid mining waste as aggregate effectively and accurately, with high R values (0.9699, 0.9619, and 0.9731 for the SVM, DT, and RF models) and lower RMSE values (SVM, DT, and RF models were 0.2332, 0.24,

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Concrete compressive strength prediction modeling ...

15/02/2021  In this research, a model has been developed to predict concrete compressive strength utilizing a detailed dataset obtained from previously published studies based on a deep learning method, namely, long short-term memory (LSTM), and a conventional machine learning (ML) algorithm, namely, support vector machine (SVM). The input variables of the model include cement, blast furnace slag,

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