concrete+compressive+strength

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:[e-mail]
TEL:[phone]

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)

混凝土抗压强度
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数据类型：多变量（multivariate）

摘要：混凝土是土木工程领域最为重要的工程材料，其抗压强度是龄期与各组分含量的高度非线性函数。所用组分包括水泥、高炉矿渣、粉煤灰、水、高效减水剂、粗骨料以及细骨料。

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数据来源：
原始数据提供者：叶义成教授（Prof. I-Cheng Yeh）
资讯管理学系，中华大学，新竹，中国台湾地区30067
电子邮箱：[e-mail]
电话：886-3-5186511

捐赠日期：2007年8月3日

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数据特征：
特定配合比下的混凝土在指定龄期（天）时的实际抗压强度（单位：兆帕（MPa））由实验室测试获得。所有数据均为原始未缩放形式。

统计摘要：
实例（观测样本）总数：1030
属性数量：9
属性构成：8个定量输入变量与1个定量输出变量
缺失属性值：无

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变量信息：
以下依次列出变量名称、数据类型、测量单位与简要说明。本数据集对应混凝土抗压强度的回归预测任务，变量列表顺序与数据库中行编号的顺序一致。

名称 -- 数据类型 -- 测量单位 -- 描述

水泥（组分1） -- 定量变量 -- 每立方米配合比中的千克数 -- 输入变量
高炉矿渣（组分2） -- 定量变量 -- 每立方米配合比中的千克数 -- 输入变量
粉煤灰（组分3） -- 定量变量 -- 每立方米配合比中的千克数 -- 输入变量
水（组分4） -- 定量变量 -- 每立方米配合比中的千克数 -- 输入变量
高效减水剂（组分5） -- 定量变量 -- 每立方米配合比中的千克数 -- 输入变量
粗骨料（组分6） -- 定量变量 -- 每立方米配合比中的千克数 -- 输入变量
细骨料（组分7） -- 定量变量 -- 每立方米配合比中的千克数 -- 输入变量
龄期 -- 定量变量 -- 天（1~365） -- 输入变量
混凝土抗压强度 -- 定量变量 -- 兆帕（MPa） -- 输出变量

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既往应用案例：
核心应用
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).
其他应用
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. I-Cheng Yeh. "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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致谢、版权信息与数据集获取：
注意：可无限制复用本数据集，但需保留对叶义成教授以及以下发表论文的版权声明：
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).

搜集汇总

背景与挑战

背景概述

该数据集名为'concrete+compressive+strength'，是一个多变量数据集，记录了混凝土的抗压强度与其成分（如水泥、矿渣、粉煤灰等）及龄期的关系。数据集包含1030个实例，9个属性（8个定量输入变量和1个定量输出变量），无缺失值，适用于回归问题研究。