An efficient Bayesian inversion method for seepage parameters using a data-driven error model and an ensemble of surrogates considering the interactions between prediction performance indicators

Yu, Hongling; Wang, Xiaoling; Ren, Bingyu; Zeng, Tuocheng; Lv, Mingming; Wang, Cheng

doi:10.1016/j.jhydrol.2021.127235

Cited by 19 publications

(9 citation statements)

References 52 publications

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“…Unlike the ordinary reversal point, the reversal point QOP is a randomly generated point between the ordinary point and the midpoint of the range of values taken by the point. The quasi-opposite number is expressed as Equation (17).…”

Section: Levy Flight Strategy and Quasi-oppositional Learning Strategymentioning

confidence: 99%

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A New Approach for Seepage Parameters Inversion Analysis Using Improved Whale Optimization Algorithm and Support Vector Regression

Li,

Shen,

Sun

et al. 2023

Applied Sciences

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Seepage is the primary cause of dam failures. Conducting regular seepage analysis for dams can effectively prevent accidents from occurring. Accurate and rapid determination of seepage parameters is a prerequisite for seepage calculation in hydraulic engineering. The Whale Optimization Algorithm (WOA) was combined with Support Vector Regression (SVR) to invert the hydraulic conductivity. The good point set initialization method, a cosine-based nonlinear convergence factor, the Levy flight strategy, and the Quasi-oppositional learning strategy were employed to improve WOA. The effectiveness and practicality of Improved Whale Optimization Algorithm (IWOA) were evaluated via numerical experiments. As a case study, the seepage parameters of the Dono Dam located on the Baishui River in China were inversed, adopting the proposed inversion model. The calculated seepage field was reasonable, and the relative error between the simulated head and the measured value at each monitoring point was within 2%. This new inversion method is more feasible and accurate than the existing hydraulic conductivity estimation methods.

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Section: Levy Flight Strategy and Quasi-oppositional Learning Strategymentioning

confidence: 99%

“…Artificial intelligence algorithms are gradually introduced into the field of hydraulic engineering [16][17][18][19][20][21]. Neaupane [22] used Matlab to construct a BP neural network model applied to landslide prediction.…”

Section: Introductionmentioning

confidence: 99%

A New Approach for Seepage Parameters Inversion Analysis Using Improved Whale Optimization Algorithm and Support Vector Regression

Li,

Shen,

Sun

et al. 2023

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…The Bayesian ranking model is a pairwise ranking optimization scheme that employs a stochastic gradient descent method as an optimization model for the parameters [19]. Based on the assumptions of Bayesian theory, the objective of the Bayesian ranking model is to maximize the posterior probability, i.e:…”

Section: Bayesian Ranking Modelmentioning

confidence: 99%

Research on the structure of corporate financial management objective system based on BRP method

Han

2023

Applied Mathematics and Nonlinear Sciences

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Exploring the architecture of corporate financial management objectives of the BRP method is to help companies achieve revenue growth. In this paper, we analyze the motivation for implementing business process reengineering and constructing an intelligent financial management system based on the BRP method and intelligent technology. The DSBPR data analysis and processing model is constructed by using Bayesian ranking model combined with similarity in heterogeneous information networks in the intelligent financial management system. The intelligent financial management system constructed in this paper is analyzed in terms of the operating capacity and profitability of the enterprise. From the viewpoint of operating capability, the turnover rate of receivables, total assets, and current assets decreased by 87.17%, 91.85% and 49.68%, respectively in ten years, and the change rate of inventory turnover was 7.91%. In terms of profitability, there is a difference of 166.12% between the maximum and minimum values of return on net assets. This shows that the use of an intelligent financial management system can provide intuitive data analysis for enterprise development, which helps enterprises to target the coordinated development of enterprise strategies and thus promote the improvement of economic returns.

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“…The rational selection of permeability coefficients is not only the core aspect of seepage behavior analysis but also a prerequisite for reliable seepage calculation results [6]. Currently, the methods for the determination of the permeability coefficients of materials primarily include the geotechnical test method [7], empirical formula method [8], and inversion analysis method [9].…”

Section: Introductionmentioning

confidence: 99%

A Novel Inversion Method for Permeability Coefficients of Concrete Face Rockfill Dam Based on Sobol-IDBO-SVR Fusion Surrogate Model

Xiong,

Shen,

et al. 2024

Mathematics

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The accurate and efficient inversion of permeability coefficients is significant for the scientific assessment of seepage safety in concrete face rockfill dams. In addressing the optimization challenge of permeability coefficients with few samples, multiple parameters, and strong nonlinearity, this paper proposes a novel intelligent inversion method based on the Sobol-IDBO-SVR fusion surrogate model. Firstly, the Sobol sequence sampling method is introduced to extract high-quality combined samples of permeability coefficients, and the equivalent continuum seepage model is utilized for the forward simulation to obtain the theoretical hydraulic heads at the seepage monitoring points. Subsequently, the support vector regression surrogate model is used to establish the complex mapping relationship between the permeability coefficients and hydraulic heads, and the convergence performance of the dung beetle optimization algorithm is effectively enhanced by fusing multiple strategies. On this basis, we successfully achieve the precise inversion of permeability coefficients driven by multi-intelligence technologies. The engineering application results show that the permeability coefficients determined based on the inversion of the Sobol-IDBO-SVR model can reasonably reflect the seepage characteristics of the concrete face rockfill dam. The maximum relative error between the measured and the inversion values of the hydraulic heads at each monitoring point is only 0.63%, indicating that the inversion accuracy meets the engineering requirements. The method proposed in this study may also provide a beneficial reference for similar parameter inversion problems in engineering projects such as bridges, embankments, and pumping stations.

show abstract

An efficient Bayesian inversion method for seepage parameters using a data-driven error model and an ensemble of surrogates considering the interactions between prediction performance indicators

Cited by 19 publications

References 52 publications

A New Approach for Seepage Parameters Inversion Analysis Using Improved Whale Optimization Algorithm and Support Vector Regression

A New Approach for Seepage Parameters Inversion Analysis Using Improved Whale Optimization Algorithm and Support Vector Regression

Research on the structure of corporate financial management objective system based on BRP method

A Novel Inversion Method for Permeability Coefficients of Concrete Face Rockfill Dam Based on Sobol-IDBO-SVR Fusion Surrogate Model

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