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
- 국제구조공학회 Smart Structures and Systems, An International Journal Smart Structures and Systems, An International Journal Vol.28 No.5
- 발행연도
- 2021.11
- 수록면
- 711 - 725 (15page)
이용수
초록· 키워드
오류제보하기
In this research, we synthesized an artificial neural network (ANN) with three metaheuristic algorithms, namely particle swarm optimization (PSO) algorithm, imperialist competition algorithm (ICA), and genetic algorithm (GA) to achieve a more accurate prediction of 28-day compressive strength of concrete. Seven input parameters (including cement, water, slag, fly ash, superplasticizer (SP), coarse aggregate (CA), and fine aggregate (FA)) were considered for this work. 80% of data (82 samples) were used to feed ANN, PSO-ANN, ICA-ANN, and GA-ANN models, and their performance was evaluated using the remaining 20% (21 samples). Referring to the executed sensitivity analysis, the best complexities for the PSO and GA were indicated by the population size = 450 and for the ICA by the population size = 400. Also, to assess the accuracy of the used predictors, the accuracy criteria of root mean square error (RMSE), coefficient of determination (R<sup>2</sup>), and mean absolute error (MAE) were defined. Based on the results, applying the PSO, ICA, and GA algorithms led to increasing R,<sup>2</sup> in the training and testing phase. Also, the MAE and RMSE of the conventional MLP experienced significant decrease after the hybridization process. Overall, the efficiency of metaheuristic science for the mentioned objective was deduced in this research. However, the combination of ANN and ICA enjoys the highest accuracy and could be a robust alternative to destructive and time-consuming tests.
목차
등록된 정보가 없습니다.
참고문헌 (91)
참고문헌 신청
Jamila M. Abdalhmid / 2019 / Long-term drying shrinkage of self-compacting concrete: Experimental and analytical investigations / Construction and Building Materials 202:825~837
Onur Akın / 2017 / Active neuro-adaptive vibration suppression of a smart beam / Smart Structures and Systems, An International Journal 20(6):657~668
Anderson, J. A. / 1995 / An Introduction to Neural Networks / MIT Press
Atashpaz-Gargari, E. / 2007 / Imperialist competitive algorithm : an algorithm for optimization inspired by imperialistic competition / 2007 IEEE Congress on Evolutionary Computation :4661~4667
Ahmet Raif Boğa / 2013 / Using ANN and ANFIS to predict the mechanical and chloride permeability properties of concrete containing GGBFS and CNI / Composites Part B: Engineering 45(1):688~696
Onur Akın / 2017 / Active neuro-adaptive vibration suppression of a smart beam / Smart Structures and Systems, An International Journal 20(6):657~668
Anderson, J. A. / 1995 / An Introduction to Neural Networks / MIT Press
Atashpaz-Gargari, E. / 2007 / Imperialist competitive algorithm : an algorithm for optimization inspired by imperialistic competition / 2007 IEEE Congress on Evolutionary Computation :4661~4667
Ahmet Raif Boğa / 2013 / Using ANN and ANFIS to predict the mechanical and chloride permeability properties of concrete containing GGBFS and CNI / Composites Part B: Engineering 45(1):688~696
함께 읽어보면 좋을 논문
논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!
-
Concrete compressive strength prediction using the imperialist competitive algorithm
Computers and Concrete, An International Journal
2018 .01
-
Optimized ANNs for predicting compressive strength of high-performance concrete
Steel and Composite Structures, An International Journal
2022 .09
-
Predicting strength of SCC using artificial neural network and multivariable regression analysis
Computers and Concrete, An International Journal
2017 .01
-
Slime mold and four other nature-inspired optimization algorithms in analyzing the concrete compressive strength
Smart Structures and Systems, An International Journal
2024 .01
-
Predicting compressive strength of bended cement concrete with ANNs
Computers and Concrete, An International Journal
2017 .01
-
Hybridized dragonfly, whale and ant lion algorithms in enlarged pile’s behavior
Smart Structures and Systems, An International Journal
2020 .01
-
Swarm-based hybridizations of neural network for predicting the concrete strength
Smart Structures and Systems, An International Journal
2020 .01
-
Ensembles of neural network with stochastic optimization algorithms in predicting concrete tensile strength
Steel and Composite Structures, An International Journal
2022 .10
-
Application of internet of things for structural assessment of concrete structures: Approach via experimental study
Smart Structures and Systems, An International Journal
2023 .01
-
Prediction of concrete strength in presence of furnace slag and fly ash using Hybrid ANN-GA (Artificial Neural Network-Genetic Algorithm)
Smart Structures and Systems, An International Journal
2020 .01
-
MLP 네트워크를 통한 3D 메쉬 텍스쳐 맵 생성 기법
한국방송미디어공학회 학술발표대회 논문집
2024 .06
-
A review study of application of artificial intelligence in construction management and composite beams
Steel and Composite Structures, An International Journal
2021 .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
-
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
-
Compressive strength of masonry structures through metaheuristics optimization algorithms
Smart Structures and Systems, An International Journal
2024 .09
-
Compressive strength prediction of limestone filler concrete using artificial neural networks
Advances in computational design
2018 .01
-
Application of Adaptive Neuro-Fuzzy Inference System for Evaluating Compressive Strength of Concrete
INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS
2021 .06
-
Residual Strength of Corroded Reinforced Concrete Beams Using an Adaptive Model Based on ANN
International Journal of Concrete Structures and Materials
2015 .06
-
Predicting the axial compressive capacity of circular concrete filled steel tube columns using an artificial neural network
Steel and Composite Structures, An International Journal
2020 .01
-
Predicting the splitting tensile strength of concrete using an equilibrium optimization model
Steel and Composite Structures, An International Journal
2021 .01
이 논문의 저자 정보
최근 본 자료
댓글(0)
0