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混凝土抗压强度数据集,用于工程建造

混凝土抗压强度数据集,用于工程建造

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Physical Regression

Data Set Information:Number of instances 1030Number of Attributes9Attribute breakdown8 quantitative input variables, and......

数据结构 ? 33K

    Data Structure ?

    * 以上分析是由系统提取分析形成的结果,具体实际数据为准。

    README.md

    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).


    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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