Utilization of Prior Information in Neural Network Training for Improving 28-Day Concrete Strength Prediction-Reference-Cited by-同舟云学术

Utilization of Prior Information in Neural Network Training for Improving 28-Day Concrete Strength Prediction

Published:2021-05 Issue:5 Volume:147 Page:04021028
ISSN:0733-9364
Container-title:Journal of Construction Engineering and Management
language:en
Short-container-title:J. Constr. Eng. Manage.

Author:

Moon Sungwoo¹,Munira Chowdhury Ayesha²^ORCID

Affiliation:

1. Professor, Dept. of Civil and Environmental Engineering, Pusan National Univ., Construction Engineering Building, Room 508, Busan 46241, Korea.

2. Ph.D. Candidate, Dept. of Civil and Environmental Engineering, Pusan National Univ., Construction Engineering Building, Room 625, Busan 46241, Korea (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Strategy and Management,Industrial relations,Building and Construction,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CO.1943-7862.0002047

Reference40 articles.

1. Pattern Classification

2. Prediction of 28-day compressive strength of concrete on the third day using artificial neural networks;Alilou V. K.;Int. J. Eng.,2010

3. Predicting the compressive strength of silica fume concrete using hybrid artificial neural network with multi-objective grey wolves

4. A modified firefly algorithm-artificial neural network expert system for predicting compressive and tensile strength of high-performance concrete

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