Concrete Compressive Strength

Donated on 8/2/2007

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

Dataset Characteristics

Multivariate

Subject Area

Physics and Chemistry

Associated Tasks

Regression

Feature Type

Real

# Instances

1030

# Features

8

Dataset Information

Additional Information

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

Has Missing Values?

No

Introductory Paper

Modeling of strength of high-performance concrete using artificial neural networks

By I. Yeh. 1998

Published in Cement and Concrete Research, Vol. 28, No. 12

Variables Table

Variable NameRoleTypeDemographicDescriptionUnitsMissing Values
CementFeatureContinuouskg/m^3no
Blast Furnace SlagFeatureIntegerkg/m^3no
Fly AshFeatureContinuouskg/m^3no
WaterFeatureContinuouskg/m^3no
SuperplasticizerFeatureContinuouskg/m^3no
Coarse AggregateFeatureContinuouskg/m^3no
Fine AggregateFeatureContinuouskg/m^3no
AgeFeatureIntegerdayno
Concrete compressive strengthTargetContinuousMPano

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Additional Variable 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

Papers Citing this Dataset

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SelectiveNet: A Deep Neural Network with an Integrated Reject Option

By Yonatan Geifman, Ran El-Yaniv. 2019

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Mixed-Integer Convex Nonlinear Optimization with Gradient-Boosted Trees Embedded

By Miten Mistry, Dimitrios Letsios, Gerhard Krennrich, Robert Lee, Ruth Misener. 2018

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Handling limited datasets with neural networks in medical applications: A small-data approach.

By Torgyn Shaikhina, Natalia Khovanova. 2017

Published in Artificial intelligence in medicine.

Learning Linear Feature Space Transformations in Symbolic Regression

By Jan vZegklitz, Petr Povs'ik. 2017

Published in ArXiv.

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15 citations
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Creators

I-Cheng Yeh

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