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Prediction of High-Performance Concrete Strength Using a Hybrid Artificial Intelligence Approach

Prayogo, Doddy and Tjong, Wong Foek and Tjandra, Daniel (2018) Prediction of High-Performance Concrete Strength Using a Hybrid Artificial Intelligence Approach. [UNSPECIFIED]

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    Abstract

    This study introduces an improved artificial intelligence (AI) approach called intelligence optimized support vector regression (IO-SVR) for estimating the compressive strength of high-performance concrete (HPC). The nonlinear functional mapping between the HPC materials and compressive strength is conducted using the AI approach. A dataset with 1,030 HPC experimental tests is used to train and validate the prediction model. Depending on the results of the experiments, the forecast outcomes of the IO-SVR model are of a much higher quality compared to the outcomes of other AI approaches. Additionally, because of the high-quality learning capabilities, the IO-SVR is highly recommended for calculating HPC strength.

    Item Type: UNSPECIFIED
    Uncontrolled Keywords: -
    Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
    T Technology > TA Engineering (General). Civil engineering (General)
    Divisions: Faculty of Civil Engineering and Planning > Civil Engineering Department
    Depositing User: Admin
    Date Deposited: 04 Nov 2018 21:25
    Last Modified: 26 Nov 2018 14:03
    URI: http://repository.petra.ac.id/id/eprint/18013

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