Article
Engineering, Civil
Jina Yin, Frank T-C Tsai, Shih-Chieh Kao
Summary: Alluvial aquifers are complex in nature and developing a reliable groundwater model for them is challenging. This study presents a Bayesian multi-model uncertainty quantification framework to account for model parameter uncertainty in alluvial groundwater modeling, improving our understanding of groundwater dynamics and prediction reliability. The methodology was applied to the agriculturally intensive Mississippi River alluvial aquifer in Northeast Louisiana, demonstrating the importance of explicitly quantifying model uncertainty in improving groundwater level predictions.
JOURNAL OF HYDROLOGY
(2021)
Article
Computer Science, Information Systems
Yong Yu, Xiaosheng Si, Changhua Hu, Jianfei Zheng, Jianxun Zhang
Summary: The study utilizes the Bayesian-updated ECM algorithm and modified Bayesian-model-averaging method to effectively address the uncertainties of model parameters and the degradation model in online RUL estimation. Simulation studies demonstrate that the proposed fusion algorithm significantly improves the prediction of gyroscope RUL.
SCIENCE CHINA-INFORMATION SCIENCES
(2021)
Article
Environmental Sciences
Pedram Darbandsari, Paulin Coulibaly
Summary: This study evaluates the impact of different hydrologic models on the performance of the hydrologic uncertainty processor (HUP) and proposes a multimodel Bayesian postprocessor (HUP-BMA). Results demonstrate the superiority of HUP-BMA in quantifying hydrologic uncertainty and forecasting compared to traditional HUP and BMA methods.
WATER RESOURCES RESEARCH
(2021)
Article
Environmental Sciences
Quanzhou Li, Yun Pan, Chong Zhang, Huili Gong
Summary: This study quantifies the uncertainties of groundwater storage (GWS) estimates in mainland China using GRACE satellites. It utilizes multiple data sources and applies the Bayesian model averaging approach to derive optimal estimates of GWS changes. The results show that the annual GWS trend in mainland China is -1.93 mm/yr with an uncertainty of 4.50 mm/yr, highlighting the importance of considering multi-source uncertainties when using GRACE data.
Article
Multidisciplinary Sciences
Anupreet Porwal, Adrian E. Raftery
Summary: Probability models are widely used in statistical tasks and it is important to choose an appropriate model and consider the uncertainty associated with this choice. This study focuses on variable selection in linear regression models and compares 21 popular methods through simulation studies. The results show that three adaptive Bayesian model averaging (BMA) methods perform the best across all statistical tasks.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Communication
Moukpe Gninigue, Kwami Ossadzifo Wonyra, Abdou-Fataou Tchagnao, Nimonka Bayale
Summary: This paper uses a panel Bayesian model averaging approach to study the impact of Information and Communication Technologies (ICTs) on developing countries' participation in Global Value Chains (GVCs). The results show that ICTs have a positive and significant effect on developing countries' participation in GVCs, which can be explained by their impact on competitive advantages such as price, product, and service. The study also explores the relationship between ICTs, other control variables, and countries' participation in GVCs using the Driscoll and Kraay estimator and Generalized Method of Moments (GMM) technique. The robust results confirm the findings of the Bayesian approach, suggesting the importance of supporting access and use of ICTs in developing countries to enhance their participation in GVCs.
TELECOMMUNICATIONS POLICY
(2023)
Article
Engineering, Industrial
Xian-Xun Yuan, Eishiro Higo, Mahesh D. Pandey
Summary: This paper presents a model to quantify the economic value gained by implementation of an inspection and preventive maintenance program, emphasizing the intricate interaction between parameter and temporal uncertainties associated with the degradation process. The research shows that the economic value is significantly sensitive to the prior information and relative costs of preventive and corrective maintenance.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Environmental Sciences
Maryam Gharekhani, Ata Allah Nadiri, Rahman Khatibi, Sina Sadeghfam, Asghar Asghari Moghaddam
Summary: Bayesian Model Averaging (BMA) was used in this study to assess groundwater vulnerability in a study area related to Lake Urmia. The results showed higher uncertainties in areas with higher vulnerability.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2022)
Article
Engineering, Civil
Sharvil Alex Faroz, Siddhartha Ghosh
Summary: This paper introduces a method to estimate the corrosion rate of reinforced concrete structures through instrument calibration using probabilistic measurement error models within a Bayesian framework and hyper-robust calibration approach. The proposed approach is demonstrated for a linear polarisation resistance instrument and found to be suitable for the study case, as well as general enough to be applied to other NDT instruments.
Article
Economics
Carlos Aller, Lorenzo Ductor, Daryna Grechyna
Summary: The study identifies GDP per capita, the share of fossil fuels in energy consumption, urbanization, industrialization, democratization, the indirect effects of trade, and political polarization as the robust determinants of CO2 emissions per capita. These determinants all negatively impact the environment except political polarization. Additionally, the determinants of CO2 emissions are found to vary depending on a country's level of income per capita.
Article
Engineering, Mechanical
Wanxin He, Gang Li, Zhaokun Nie
Summary: A sparse PDD metamodel based on Bayesian LASSO and adaptive candidate basis selection and model updating method is proposed in this study, which can improve computational accuracy when design samples are limited.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Engineering, Environmental
Mi Tian, Hao Fan, Zimin Xiong, Lihua Li
Summary: Accurate and reliable predictions of debris-flow volume are crucial for assessing potential hazards and risks. This paper proposes a data-driven ensemble model that combines deterministic machine learning methods and Bayesian model averaging to probabilistically forecast debris-flow volume. The feasibility of the approach is demonstrated using rainfall-induced debris flows in Taiwan, and the performance of individual models and the ensemble model is evaluated.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
(2023)
Article
Environmental Sciences
Young Hoon Song, Eun-Sung Chung, Shamsuddin Shahid
Summary: This study compares the performance of LSTM networks and SWAT in simulating observed runoff and projecting future runoff. The results show that LSTM has better capability in reproducing observed runoff and estimating future runoff.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Computer Science, Interdisciplinary Applications
David Reynolds, Luis Carvalho
Summary: A novel approach to statistical inference for multivariate binary transaction data is proposed in this study. The hierarchical model and MCMC sampling procedure provided a sparser representation of item associations compared to frequent itemset mining, without sacrificing predictive accuracy. By allowing inference on a broad set of parameters, the model offers a deeper level of insight into transaction data.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2021)
Article
Business, Finance
Zhao -Chen Li, Chi Xie, Gang-Jin Wang, You Zhu, Jian-You Long, Yang Zhou
Summary: Model uncertainty plays a crucial role in predicting stock market volatility compared to parameter uncertainty. Combination models with model uncertainty, especially dynamic model averaging (DMA), provide competitive improvements in forecasting accuracy and are also effective in asset allocation and risk hedging.
RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE
(2023)
Article
Agronomy
Yang Yang, Yan Zhu, Jingwei Wu, Wei Mao, Ming Ye, Jinzhong Yang
Summary: A new subsurface drainage (SDR) package based on the Hooghoudt equation was developed to accurately simulate the effects of subsurface drainage pipes on groundwater flow and salt dynamics. The accuracy and applicability of SDR were tested through synthetic and field experiments, demonstrating its ability to accurately model leaching water and solute transport. Applied in the Yonglian irrigation area of Inner Mongolia, China, the SDR system increased total salt discharge by 38-54%, with 36-45% discharged by subsurface drainage pipes, providing a pilot example for regional subsurface drainage system design.
AGRICULTURAL WATER MANAGEMENT
(2022)
Article
Engineering, Multidisciplinary
Jing Hu, Qimin Zhang, Anke Meyer-Baese, Ming Ye
Summary: This study introduces a new model to address the increasing prevalence of Alzheimer's disease in today's society, using a stochastic reaction-diffusion approach to calculate the progression of AD and providing conditions for finite-time stability. Furthermore, an optimal control problem is formulated to minimize pathogenic proteins and control costs, with specific examples provided for demonstration.
APPLIED MATHEMATICAL MODELLING
(2022)
Article
Geosciences, Multidisciplinary
Jing Yang, Honghua Liu, Zhonghua Tang, Luk Peeters, Ming Ye
Summary: Graphical methods are commonly used in the analysis of aqueous geochemical data. WQChartPy is an open-source Python package that provides 12 different diagrams for visualizing and interpreting such data. It supports various data formats and allows the generated diagrams to be saved in different file formats.
Article
Engineering, Civil
Jing Yang, Ming Ye
Summary: This study introduces a new sensitivity analysis method called MMADS, which is capable of screening non-influential hydrologic processes and parameters. It addresses both process model uncertainty and model parameter uncertainty, and demonstrates good performance in two numerical experiments.
JOURNAL OF HYDROLOGY
(2022)
Article
Environmental Sciences
Guanfang Sun, Yan Zhu, Ming Ye, Yang Yang, Jinzhong Yang, Wei Mao, Jingwei Wu
Summary: This study conducted soil salinity measurements at 68 sampling sites at different depths and utilized geostatistical analysis and temporal stability analysis to understand soil salinity variability. It found strong spatial dependency of soil salinity, proposed an improved temporal stability analysis method, and achieved significantly improved predictions. The study recommends combining these analytical methods for better monitoring efficiency of regional soil salinity.
JOURNAL OF SOILS AND SEDIMENTS
(2022)
Article
Engineering, Civil
Mengqin Wang, Yan Zhu, Tianxing Zhao, Lihong Cui, Wei Mao, Ming Ye, Jingwei Wu, Jinzhong Yang
Summary: Field experiments were conducted to analyze the non-synchronized movement of soil water and salt during freezing-thawing periods, with a focus on soil salt composition and convection-diffusion theory. The results shed light on the mechanisms underlying soil water and salt dynamics in agricultural systems with shallow groundwater tables.
JOURNAL OF HYDROLOGY
(2022)
Article
Mathematics, Applied
Wenrui Li, Ming Ye, Qimin Zhang, Meyer-Baese Anke, Yan Li
Summary: This paper introduces a periodic averaging method for impulsive stochastic age-structured population models in a polluted environment. It demonstrates the uniqueness of the solutions and the mean-square convergence criteria of numerical solutions, and validates the efficiency of the method through a simulation example.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2022)
Article
Engineering, Mechanical
Jing Hu, Qimin Zhang, Anke Meyer-Baese, Ming Ye
Summary: In this paper, a stochastic model is proposed to describe the dynamics of substances related to Alzheimer's disease. The theoretical results are validated by numerical simulations.
NONLINEAR DYNAMICS
(2022)
Article
Environmental Sciences
Tian Jiao, Ming Ye, Menggui Jin, Jing Yang
Summary: The Smoothed Particle Hydrodynamics (SPH) method is a Lagrangian approach widely used for solving numerical dispersion problems in groundwater solute transport. To improve accuracy in models with irregular particle distribution, an Interactively Corrected SPH (IC-SPH) method was developed. IC-SPH uses interactively corrected kernel gradients to construct concentration gradients, resulting in more accurate and faster converging solutions.
WATER RESOURCES RESEARCH
(2022)
Article
Mathematics, Applied
Wenjuan Guo, Qimin Zhang, Ming Ye
Summary: This paper develops an age-structured HIV model considering age of infected cells and intracellular delay, and a stochastic age-structured HIV model with Markovian switching to study finite-time contraction stability. Theoretical and numerical results illustrate the impact of noise intensity and delay on stability of the HIV models.
Article
Environmental Sciences
Tian Jiao, Ming Ye, Menggui Jin, Jing Yang
Summary: This study develops a Decoupled Finite Particle Method with Normalized Kernel (DFPM-NK) to improve the computational accuracy of solute transport simulations. Through comparing the computational performance of several methods, it is found that DFPM-NK is more efficient than FPM with similar accuracy. Therefore, it is recommended to use DFPM-NK for computationally expensive solute transport problems.
WATER RESOURCES RESEARCH
(2022)
Article
Mathematics, Applied
Yanyan Du, Ming Ye, Qimin Zhang
Summary: This paper develops a model describing a stochastic age-dependent population system with Levy noise in a polluted environment, and proposes a numerical algorithm based on a modified truncated Euler-Maruyama method to maintain positivity. The study focuses on global positivity analysis, finite element method, and convergence error estimates of the numerical schemes under suitable regularity conditions. A numerical example is provided to illustrate the theoretical results.
COMPUTERS & MATHEMATICS WITH APPLICATIONS
(2022)
Article
Engineering, Civil
Yan Zhu, Tianxing Zhao, Wei Mao, Ming Ye, Xudong Han, Biao Jia, Jinzhong Yang
Summary: A modified UBMOD flow model was developed to accurately estimate soil water content and water table depth in arid agricultural areas with shallow water table depth. The model incorporates the impact of capillary rise and calculates water table depth using the water table depth fluctuation analysis. The results demonstrated its effectiveness and low computational cost, making it a valuable tool for hydrodynamic studies in areas with shallow water table depths.
JOURNAL OF HYDROLOGY
(2023)
Article
Engineering, Civil
Mengqin Wang, Yan Zhu, Wei Mao, Ming Ye, Jinzhong Yang
Summary: Current research on soil salt movement during the freeze and thaw period has focused mainly on total salt concentration, neglecting the phase change of multi-component salts. This study investigated the potential transport capability of soil water and salt ions in the frozen layer using chemical characteristics and solute convection-diffusion theory. Field experiments were conducted to measure changes in total soil water, soil salt, and its ion components. The results showed different migration directions and quantities of various salt ions due to concentration gradients and diffusion coefficients, with Na+, Cl-, and SO42- exhibiting larger potential convection and dispersion quantities than Ca2+, Mg2+, and HCO3-. This study provides a new perspective on soil salt movement in frozen agricultural areas with shallow groundwater tables.
JOURNAL OF HYDROLOGY
(2023)
Article
Mathematics, Applied
Yanyan Du, Ming Ye, Qimin Zhang
Summary: In this paper, a stochastic population-toxicant model with cross-diffusion is developed and the local boundedness of strong solutions is studied. The existence of a global martingale solution in a Hilbert space is obtained using the Galerkin approximation method, the tightness criterion, and the energy estimation.
APPLIED MATHEMATICS LETTERS
(2023)