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Information Journal Paper

Title

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM AND STEPWISE REGRESSION FOR COMPRESSIVE STRENGTH ASSESSMENT OF CONCRETE CONTAINING METAKAOLIN

Author(s)

  SHARIFI Y. | HOSSEINPOUR M.

Pages

  251-272

Keywords

adaptive neuro-fuzzy inference system (ANFIS) 
stepwise regression (SR) 

Abstract

 In the current study two methods are evaluated for predicting the compressive strength of concrete containing metakaolin. Adaptive neuro-fuzzy inference system (ANFIS) model and stepwise regression (SR) model are developed as a reliable modeling method for simulating and predicting the compressive strength of concrete containing metakaolin at the different ages. The required data in training and testing state obtained from a reliable data base. Then, a comparison has been made between proposed ANFIS model and SR model to have an idea about the predictive power of these methods.

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    APA: Copy

    SHARIFI, Y., & HOSSEINPOUR, M.. (2019). ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM AND STEPWISE REGRESSION FOR COMPRESSIVE STRENGTH ASSESSMENT OF CONCRETE CONTAINING METAKAOLIN. INTERNATIONAL JOURNAL OF OPTIMIZATION IN CIVIL ENGINEERING, 9(2), 251-272. SID. https://sid.ir/paper/329500/en

    Vancouver: Copy

    SHARIFI Y., HOSSEINPOUR M.. ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM AND STEPWISE REGRESSION FOR COMPRESSIVE STRENGTH ASSESSMENT OF CONCRETE CONTAINING METAKAOLIN. INTERNATIONAL JOURNAL OF OPTIMIZATION IN CIVIL ENGINEERING[Internet]. 2019;9(2):251-272. Available from: https://sid.ir/paper/329500/en

    IEEE: Copy

    Y. SHARIFI, and M. HOSSEINPOUR, “ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM AND STEPWISE REGRESSION FOR COMPRESSIVE STRENGTH ASSESSMENT OF CONCRETE CONTAINING METAKAOLIN,” INTERNATIONAL JOURNAL OF OPTIMIZATION IN CIVIL ENGINEERING, vol. 9, no. 2, pp. 251–272, 2019, [Online]. Available: https://sid.ir/paper/329500/en

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