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 제33권 제1호
- 발행연도
- 2024.1
- 수록면
- 65 - 91 (27page)
이용수
초록· 키워드
오류제보하기
The use of five optimization techniques for the prediction of a strength-based concrete mixture's best-fit model is examined in this work. Five optimization techniques are utilized for this purpose: Slime Mold Algorithm (SMA), Black Hole Algorithm (BHA), Multi-Verse Optimizer (MVO), Vortex Search (VS), and Whale Optimization Algorithm (WOA). MATLAB employs a hybrid learning strategy to train an artificial neural network that combines least square estimation with backpropagation. Thus, 72 samples are utilized as training datasets and 31 as testing datasets, totaling 103. The multi-layer perceptron (MLP) is used to analyze all data, and results are verified by comparison. For training datasets in the best-fit models of SMAMLP, BHA-MLP, MVO-MLP, VS-MLP, and WOA-MLP, the statistical indices of coefficient of determination (R<sup>2</sup>) in training phase are 0.9603, 0.9679, 0.9827, 0.9841 and 0.9770, and in testing phase are 0.9567, 0.9552, 0.9594, 0.9888 and 0.9695 respectively. In addition, the best-fit structures for training for SMA, BHA, MVO, VS, and WOA (all combined with multilayer perceptron, MLP) are achieved when the term population size was modified to 450, 500, 250, 150, and 500, respectively. Among all the suggested options, VS could offer a stronger prediction network for training MLP.
목차
등록된 정보가 없습니다.
참고문헌 (0)
참고문헌 신청함께 읽어보면 좋을 논문
논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!
-
Hybridized dragonfly, whale and ant lion algorithms in enlarged pile’s behavior
Smart Structures and Systems, An International Journal
2020 .01
-
Predicting the concrete compressive strength through MLP network hybridized with three evolutionary algorithms
Smart Structures and Systems, An International Journal
2021 .11
-
Metaheuristic-reinforced neural network for predicting the compressive strength of concrete
Smart Structures and Systems, An International Journal
2022 .08
-
Swarm-based hybridizations of neural network for predicting the concrete strength
Smart Structures and Systems, An International Journal
2020 .01
-
Prediction of fly ash concrete compressive strengths using soft computing techniques
Computers and Concrete, An International Journal
2020 .01
-
MLP 네트워크를 통한 3D 메쉬 텍스쳐 맵 생성 기법
한국방송미디어공학회 학술발표대회 논문집
2024 .06
-
Ensembles of neural network with stochastic optimization algorithms in predicting concrete tensile strength
Steel and Composite Structures, An International Journal
2022 .10
-
Prediction of the compressive strength of fly ash geopolymer concrete using gene expression programming
Computers and Concrete, An International Journal
2019 .01
-
Optimized ANNs for predicting compressive strength of high-performance concrete
Steel and Composite Structures, An International Journal
2022 .09
-
다층 퍼셉트론의 네트워크 아키텍쳐 결정을 위한 빅데이터 기반 효율적인 탐색 기법
대한기계학회 춘추학술대회
2020 .12
-
MLP 학습 자동화 프로그램
한국지능정보시스템학회 학술대회논문집
2016 .11
-
단일 카메라 영상을 이용한 MLP 기반 변형률 예측 기법
대한건축학회 학술발표대회 논문집
2022 .10
-
Predicting the Performance of Blower Systems using Multi-Layer-Perceptron(MLP) Architecture with Real Data
한국유체기계학회 학술대회 논문집
2024 .12
-
MLP(Multi-Layer Perceptron)를 활용한 ESS 연계 태양광 발전량 예측 기술 연구
대한전기학회 학술대회 논문집
2024 .07
-
MLP 기반의 2D LiDAR를 이용한 보행자 검출 네트워크
대한전자공학회 학술대회
2019 .06
-
표준비행데이터 생성을 위한 MLP 적용
항공우주시스템공학회 학술행사 논문집
2024 .10
-
Automatic Music Mood Detection Using Transfer Learning and Multilayer Perceptron
INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS
2019 .06
-
빅데이터를 활용한 하절기 평일의 시간대별 전력부하예측 신경망 모형
조명·전기설비학회논문지
2019 .12
-
뇌파와 MLP 알고리즘을 이용한 치매 진단에 대한 연구
대한기계학회 춘추학술대회
2018 .04
-
Comparison and optimization of deep learning-based radiosensitivity prediction models using gene expression profiling in National Cancer Institute-60 cancer cell line
Nuclear Engineering and Technology
2022 .08
최근 본 자료
댓글(0)
0