Bayesian reliability-based prediction of the soil water retention curve using finite data
文献类型：期刊论文
| 作者 | Onyekwena, Chikezie Chimere1,3; Li, Qi1,3 ; Umeobi, Happiness Ijeoma1,3,4; Li, Xiaying1,3; Ng'ombe, John N.2
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| 刊名 | EXPERT SYSTEMS WITH APPLICATIONS
 |
| 出版日期 | 2022-10-01 |
| 卷号 | 203期号:-页码:- |
| 关键词 | Bayesian framework Markov chain Monte Carlo Hamiltonian Monte Carlo Finite data Soil water retention curve |
| ISSN号 | 0957-4174 |
| 英文摘要 | The soil water retention curve (SWRC) is a core concept of unsaturated soil mechanics. To date, while various SWRC prediction models have been developed, they require large datasets to generate accurate results. Most importantly, and uncoincidentally, obtaining large SWRC datasets from experimental procedures might prove costly, time-consuming, and sometimes rigorous; thus, making only limited data available for use. However, determining the inherent uncertainties in predictions when using finite data has been elusive. To address this problem, we propose a reliability-based approach using a Bayesian framework that is logical and rigorous for quantifying uncertainty in model parameters. The proposed Bayesian method is Hamiltonian Monte Carlo (HMC). The HMC is a Markov chain Monte Carlo (MCMC) method that applies the Hamiltonian dynamics to solve and update posterior distributions in Bayesian analysis. Different SWRC datasets and models were used to validate and test the efficacy and robustness of the model in making predictions. The results show that the method is so robust that even imperfect prior knowledge provides reliable SWRC prediction results comparable with other methods. Furthermore, computation time and cost are significantly reduced because of the small (MCMC) sample size required to complete numerical solutions. |
| 学科主题 | Computer Science ; Engineering ; Operations Research & Management Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000803570800001 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| 源URL | [http://119.78.100.198/handle/2S6PX9GI/35363]  |
| 专题 | 中科院武汉岩土力学所 |
| 作者单位 | 1.University of Chinese Academy of Sciences, Beijing 100049, China 2.Department of Agribusiness, Applied Economics, and Agriscience Education, North Carolina A&T State University, NC, USA 3.State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan 430071, China 4.Nnamdi Azikiwe University, Awka, Nigeria |
| 推荐引用方式 GB/T 7714 | Onyekwena, Chikezie Chimere,Li, Qi,Umeobi, Happiness Ijeoma,et al. Bayesian reliability-based prediction of the soil water retention curve using finite data[J]. EXPERT SYSTEMS WITH APPLICATIONS,2022,203(-):-. |
| APA | Onyekwena, Chikezie Chimere,Li, Qi,Umeobi, Happiness Ijeoma,Li, Xiaying,&Ng'ombe, John N..(2022).Bayesian reliability-based prediction of the soil water retention curve using finite data.EXPERT SYSTEMS WITH APPLICATIONS,203(-),-. |
| MLA | Onyekwena, Chikezie Chimere,et al."Bayesian reliability-based prediction of the soil water retention curve using finite data".EXPERT SYSTEMS WITH APPLICATIONS 203.-(2022):-. |
入库方式： OAI收割
来源：武汉岩土力学研究所
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