Concrete Compressive Strength
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Data Type: multivariate
Abstract: Concrete is the most important material in civil engineering. The
concrete compressive strength is a highly nonlinear function of age and
ingredients. These ingredients include cement, blast furnace slag, fly ash,
water, superplasticizer, coarse aggregate, and fine aggregate.
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Sources:
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
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Data Characteristics:
The actual concrete compressive strength (MPa) for a given mixture under a
specific age (days) was determined from laboratory. Data is in raw form (not scaled).
Summary Statistics:
Number of instances (observations): 1030
Number of Attributes: 9
Attribute breakdown: 8 quantitative input variables, and 1 quantitative output variable
Missing Attribute Values: None
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Variable Information:
Given is 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
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Past Usage:
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?.
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Acknowledgements, Copyright Information, and Availability:
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)