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Concrete Compressive Strength Data Set
Download: Data Folder, Data Set Description

Abstract: Concrete is the most important material in civil engineering. The concrete compressive strength is a highly nonlinear function of age and ingredients.

Data Set Characteristics:  

Multivariate

Number of Instances:

1030

Area:

Physical

Attribute Characteristics:

Real

Number of Attributes:

9

Date Donated

2007-08-03

Associated Tasks:

Regression

Missing Values?

N/A

Number of Web Hits:

82101


Source:

Original Owner and Donor
Prof. I-Cheng Yeh
Department of Information Management
Chung-Hua University,
Hsin Chu, Taiwan 30067, R.O.C.
e-mail:icyeh '@' chu.edu.tw
TEL:886-3-5186511

Date Donated: August 3, 2007


Data Set Information:

Number of instances 1030
Number of Attributes 9
Attribute breakdown 8 quantitative input variables, and 1 quantitative output variable
Missing Attribute Values None


Attribute Information:

Given are the variable name, variable type, the measurement unit and a brief description. The concrete compressive strength is the regression problem. The order of this listing corresponds to the order of numerals along the rows of the database.

Name -- Data Type -- Measurement -- Description

Cement (component 1) -- quantitative -- kg in a m3 mixture -- Input Variable
Blast Furnace Slag (component 2) -- quantitative -- kg in a m3 mixture -- Input Variable
Fly Ash (component 3) -- quantitative -- kg in a m3 mixture -- Input Variable
Water (component 4) -- quantitative -- kg in a m3 mixture -- Input Variable
Superplasticizer (component 5) -- quantitative -- kg in a m3 mixture -- Input Variable
Coarse Aggregate (component 6) -- quantitative -- kg in a m3 mixture -- Input Variable
Fine Aggregate (component 7) -- quantitative -- kg in a m3 mixture -- Input Variable
Age -- quantitative -- Day (1~365) -- Input Variable
Concrete compressive strength -- quantitative -- MPa -- Output Variable


Relevant Papers:

Main
1. I-Cheng Yeh, "Modeling of strength of high performance concrete using artificial neural networks," Cement and Concrete Research, Vol. 28, No. 12, pp. 1797-1808 (1998).

Others
2. I-Cheng Yeh, "Modeling Concrete Strength with Augment-Neuron Networks," J. of Materials in Civil Engineering, ASCE, Vol. 10, No. 4, pp. 263-268 (1998).
3. I-Cheng Yeh, "Design of High Performance Concrete Mixture Using Neural Networks," J. of Computing in Civil Engineering, ASCE, Vol. 13, No. 1, pp. 36-42 (1999).
4. I-Cheng Yeh, "Prediction of Strength of Fly Ash and Slag Concrete By The Use of Artificial Neural Networks," Journal of the Chinese Institute of Civil and Hydraulic Engineering, Vol. 15, No. 4, pp. 659-663 (2003).
5. I-Cheng Yeh, "A mix Proportioning Methodology for Fly Ash and Slag Concrete Using Artificial Neural Networks," Chung Hua Journal of Science and Engineering, Vol. 1, No. 1, pp. 77-84 (2003).
6. Yeh, I-Cheng, "Analysis of strength of concrete using design of experiments and neural networks," Journal of Materials in Civil Engineering, ASCE, Vol.18, No.4, pp.597-604 (2006).



Citation Request:

NOTE: Reuse of this database is unlimited with retention of copyright notice for Prof. I-Cheng Yeh and the following published paper:

I-Cheng Yeh, "Modeling of strength of high performance concrete using artificial neural networks," Cement and Concrete Research, Vol. 28, No. 12, pp. 1797-1808 (1998).


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