지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국계산역학회 Computers and Concrete, An International Journal Computers and Concrete, An International Journal Vol.25 No.5
- 발행연도
- 2020.1
- 수록면
- 401 - 409 (9page)
이용수
초록· 키워드
오류제보하기
Artificial neural networks are used as a useful tool in distinct fields of civil engineering these days. In order to control long-term quality of Self-Compacting Semi-Lightweight Concrete (SCSLC), the 90 days compressive strength is considered as a key issue in this paper. In fact, combined artificial neural networks are used to predict the compressive strength of SCSLC at 28 and 90 days. These networks are able to re-establish non-linear and complex relationships straightforwardly. In this study, two types of neural networks, including Radial Basis and Multilayer Perceptron, were used. Four groups of concrete mix designs also were made with two water to cement ratios (W/C) of 0.35 and 0.4, as well as 10% of cement weight was replaced with silica fume in half of the mixes, and different amounts of superplasticizer were used. With the help of rheology test and compressive strength results at 7 and 14 days as inputs, the neural networks were used to estimate the 28 and 90 days compressive strengths of above-mentioned mixes. It was necessary to add the 14 days compressive strength in the input layer to gain acceptable results for 90 days compressive strength. Then proper neural networks were prepared for each mix, following which four existing networks were combined, and the combinatorial neural network model properly predicted the compressive strength of different mix designs.
목차
등록된 정보가 없습니다.
참고문헌 (44)
참고문헌 신청
1998 / ACI 213 R-87, Guide for Structural Lightweight Aggregate Concrete
Oveys Afzali Naniz / 2018 / Effects of colloidal nano-silica on fresh and hardened properties of self-compacting lightweight concrete / Journal of Building Engineering 20:400~410
Oveys Afzali-Naniz / 2019 / Assessment of the influence of micro- and nano-silica on the behavior of self-compacting lightweight concrete using full factorial design / Asian Journal of Civil Engineering 20(1):57~70
Oveys Afzali-Naniz / 2019 / Fracture behavior of self-compacting semi-lightweight concrete containing nano-silica / Advances in Structural Engineering 22(10):2264~2277
Marai M. Alshihri / 2009 / Neural networks for predicting compressive strength of structural light weight concrete / Construction and Building Materials 23(6):2214~2219
Oveys Afzali Naniz / 2018 / Effects of colloidal nano-silica on fresh and hardened properties of self-compacting lightweight concrete / Journal of Building Engineering 20:400~410
Oveys Afzali-Naniz / 2019 / Assessment of the influence of micro- and nano-silica on the behavior of self-compacting lightweight concrete using full factorial design / Asian Journal of Civil Engineering 20(1):57~70
Oveys Afzali-Naniz / 2019 / Fracture behavior of self-compacting semi-lightweight concrete containing nano-silica / Advances in Structural Engineering 22(10):2264~2277
Marai M. Alshihri / 2009 / Neural networks for predicting compressive strength of structural light weight concrete / Construction and Building Materials 23(6):2214~2219
함께 읽어보면 좋을 논문
논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!
-
Predicting strength of SCC using artificial neural network and multivariable regression analysis
Computers and Concrete, An International Journal
2017 .01
-
Compressive strength prediction of limestone filler concrete using artificial neural networks
Advances in computational design
2018 .01
-
The prediction of compressive strength and non-destructive tests of sustainable concrete by using artificial neural networks
Computers and Concrete, An International Journal
2021 .01
-
Portland cement structure and its major oxides and fineness
Smart Structures and Systems, An International Journal
2018 .01
-
Application of internet of things for structural assessment of concrete structures: Approach via experimental study
Smart Structures and Systems, An International Journal
2023 .01
-
Optimization of Curing Regimes for Precast Prestressed Members with Early-Strength Concrete
International Journal of Concrete Structures and Materials
2016 .09
-
Optimization of cost and mechanical properties of concrete with admixtures using MARS and PSO
Computers and Concrete, An International Journal
2020 .01
-
Prediction of compressive strength of concrete based on accelerated strength
Structural engineering and mechanics : An international journal
2016 .01
-
Study on the applicability of regression models and machine learning models for predicting concrete compressive strength
Structural Engineering and Mechanics, An Int＇l Journal
2024 .09
-
Concrete compressive strength prediction using the imperialist competitive algorithm
Computers and Concrete, An International Journal
2018 .01
-
Artificial Neural Network with Complex Structures
한국통신학회 학술대회논문집
2020 .08
-
Predicting compressive strength of bended cement concrete with ANNs
Computers and Concrete, An International Journal
2017 .01
-
Predicting the compressive strength of self-compacting concrete containing fly ash using a hybrid artificial intelligence method
Computers and Concrete, An International Journal
2018 .01
-
Long-term development of compressive strength and elastic modulus of concrete
Structural engineering and mechanics : An international journal
2018 .01
-
Artificial neural network calculations for a receding contact problem
Computers and Concrete, An International Journal
2020 .01
-
A neural-based predictive model of the compressive strength of waste LCD glass concrete
Computers and Concrete, An International Journal
2017 .01
-
초고강도 콘크리트의 압축강도 특성에 관한 문헌적 고찰
대한건축학회 학술발표대회 논문집
2016 .04
-
학교 실내 PM2.5 농도 예측모델 개발
대한건축학회 학술발표대회 논문집
2021 .04
-
Failure characteristics of columns intersected by slabs with different compressive strengths
Structural Engineering and Mechanics, An Int＇l Journal
2020 .01
-
조강형 시멘트의 광물조성, 분말도, SO₃ 함량이 모르타르 및 콘크리트 압축강도에 미치는 영향
대한건축학회논문집
2022 .02
이 논문의 저자 정보
최근 본 자료
댓글(0)
0