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Evaluation of liquefaction-induced lateral displacement using Bayesian belief networks

Mahmood AHMAD, Xiao-Wei TANG, Jiang-Nan QIU, Feezan AHMAD

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 1,   Pages 80-98 doi: 10.1007/s11709-021-0682-3

Abstract: a novel probabilistic framework for evaluating liquefaction-induced lateral displacement using the Bayesianbelief network (BBN) approach based on an interpretive structural modeling technique.

Keywords： Bayesian belief network     seismically induced soil liquefaction     interpretive structural modeling     lateral    

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A knowledge reasoning Fuzzy-Bayesian network for root cause analysis of abnormal aluminum electrolysis

Weichao Yue, Xiaofang Chen, Weihua Gui, Yongfang Xie, Hongliang Zhang

Frontiers of Chemical Science and Engineering 2017, Volume 11, Issue 3,   Pages 414-428 doi: 10.1007/s11705-017-1663-x

Abstract: In view of this, a method based on Fuzzy-Bayesian network to construct multi-source knowledge solidificationcause analysis by finding the abnormal state of root node, which has a maximum posterior probability by Bayesian

Keywords： abnormal aluminum electrolysis cell condition     Fuzzy-Bayesian network     multi-source knowledge solidification    

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A case study on sample average approximation method for stochastic supply chain network design problem

Yuan WANG, Ruyan SHOU, Loo Hay LEE, Ek Peng CHEW

Frontiers of Engineering Management 2017, Volume 4, Issue 3,   Pages 338-347 doi: 10.15302/J-FEM-2017032

Abstract: This study aims to solve a typical long-term strategic decision problem on supply chain network designnonanticipativity constraints, branch-and-fix coordination, sample average approximation (SAA) with BayesianA computational study of supply chain network with front-ends in Europe and back-ends in Asia is presented

Keywords： supply chain network     stochastic demand     sampling average approximation     Bayesian bootstrap     Latin hypercube    

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A Bayesian modeling approach to bi-directional pedestrian flows in carnival events

S. Q. XIE, S. C. WONG, William H. K. LAM

Frontiers of Engineering Management 2017, Volume 4, Issue 4,   Pages 483-489 doi: 10.15302/J-FEM-2017023

Abstract: Bayesian inference was employed to calibrate the model by using prior data obtained from a previous controlled

Keywords： pedestrian flow model     bi-directional interactions     empirical studies     Bayesian inference    

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An assessment of surrogate fuel using Bayesian multiple kernel learning model in sight of sooting tendency

Frontiers in Energy 2022, Volume 16, Issue 2,   Pages 277-291 doi: 10.1007/s11708-021-0731-6

Abstract: values for surrogate fuels was proposed with the application of a machine learning method, named the Bayesian

Keywords： sooting tendency     yield sooting index     Bayesian multiple kernel learning     surrogate assessment     surrogate    

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Identification of pollution sources in rivers using a hydrodynamic diffusion wave model and improved Bayesian-Markov

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 7, doi: 10.1007/s11783-023-1685-1

Abstract:

● A hydrodynamic-Bayesian inference model was developed for water

Keywords： Identification of pollution sources     Water quality restoration     Bayesian inference     Hydrodynamic model    

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Hybrid Bayesian Network Method for Predicting Intrusion

Wang Liangmin, Ma Jianfeng

Strategic Study of CAE 2008, Volume 10, Issue 8,   Pages 87-96

Abstract: network method is presented in this paper.Secondly, a hybrid Bayesian network model based on this intrusion model is presented to show the casualIn this hybrid Bayesian network model, the connections of the same layer are continuous, but that ofThe algorithm for computing the joint probability distribution of the hybrid Bayesian network is presentedIn the end, the efficiency of the intrusion model and hybrid Bayesian network in predicting intrusion

Keywords： intrusion tolerance     alert correlation     intrusion model     intrusion prediction    

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Controller area network node reliability assessment based on observable node information Article

Lei-ming ZHANG, Long-hao TANG, Yong LEI

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 5,   Pages 615-626 doi: 10.1631/FITEE.1601029

Abstract: Controller area network (CAN) based fieldbus technologies have been widely used in networked manufacturingThe method estimates the transmit error counter (TEC) of any node in the network based on the networkIt considers the sparseness of the distribution of the CAN network errors.learning the differences between the model estimates and the actual values from the observable node, a Bayesiannetwork is developed for the estimation updating mechanism of the observable nodes.

Keywords： Controller area network (CAN)     Transmit error counter (TEC)     TEC value estimation     Bayesian network    

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Quality-related locally weighted soft sensing for non-stationary processes by a supervised Bayesian network Research Articles

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 9,   Pages 1234-1246 doi: 10.1631/FITEE.2000426

Abstract: quality-related locally weighted soft sensing method is designed for non-stationary processes based on a Bayesiannetwork with .

Keywords： 软测量；有监督贝叶斯网络；隐变量；局部加权建模；质量预测    

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Short-term Load Forecasting Using Neural Network

Luo Mei

Strategic Study of CAE 2007, Volume 9, Issue 5,   Pages 77-80

Abstract: the optimized function,  an optimized L-M algorithm, which can accelerate the training of neural network Bayesian regularization can overcome the over fitting and improve the generalization of ANN.

Keywords： short-term load forecasting(STLF)     ANN     Levenberg-Marquardt     Bayesian regularization     optimized algorithms    

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Application of machine learning algorithms for the evaluation of seismic soil liquefaction potential

Mahmood AHMAD, Xiao-Wei TANG, Jiang-Nan QIU, Feezan AHMAD, Wen-Jing GU

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 2,   Pages 490-505 doi: 10.1007/s11709-020-0669-5

Abstract: liquefaction potential of soil based on the cone penetration test field case history records using the Bayesianbelief network (BBN) learning software Netica.

Keywords： seismic soil liquefaction     Bayesian belief network     cone penetration test     parameter learning     structural    

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A novel multimode process monitoring method integrating LDRSKM with Bayesian inference

Shi-jin REN,Yin LIANG,Xiang-jun ZHAO,Mao-yun YANG

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 8,   Pages 617-633 doi: 10.1631/FITEE.1400263

Abstract: A local discriminant regularized soft -means (LDRSKM) method with Bayesian inference is proposed forTwo Bayesian inference based global fault detection indicators are then developed using the local monitoringBased on clustering analysis, Bayesian inference and manifold learning methods, the within and cross-mode

Keywords： monitoring     Local discriminant regularized soft k-means clustering     Kernel support vector data description     Bayesian    

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A Probabilistic Architecture of Long-Term Vehicle Trajectory Prediction for Autonomous Driving Article

Jinxin Liu, Yugong Luo, Zhihua Zhong, Keqiang Li, Heye Huang, Hui Xiong

Engineering 2022, Volume 19, Issue 12,   Pages 228-239 doi: 10.1016/j.eng.2021.12.020

Abstract: DIM is designed and employed to accurately infer the potential driving intention based on a dynamic Bayesiannetwork.

Keywords： Autonomous driving     Dynamic Bayesian network     Driving intention recognition     Gaussian process     Vehicle    

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Data-Driven Model Falsification and Uncertainty Quantification for Fractured Reservoirs Article

Junling Fang, Bin Gong, Jef Caers

Engineering 2022, Volume 18, Issue 11,   Pages 116-128 doi: 10.1016/j.eng.2022.04.015

Abstract: Bayesian theorem provides a framework to quantify the uncertainty in geological modeling and flow simulationThe application of Bayesian methods to fractured reservoirs has mostly been limited to synthetic casesIn field applications, however, one of the main problems is that the Bayesian prior is falsified, becauseWe then employ an approximate Bayesian computation (ABC) method combined with a tree-based surrogate

Keywords： Bayesian evidential learning     Falsification     Fractured reservoir     Random forest     Approximate Bayesian computation    

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Variational Bayesian multi-sparse component extraction for damage reconstruction of space debris hypervelocity Research Article

Xuegang HUANG, Anhua SHI, Qing LUO, Jinyang LUO,emei-126@126.com

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 4,   Pages 530-541 doi: 10.1631/FITEE.2000575

Abstract: To improve the survivability of orbiting spacecraft against space debris impacts, we propose an impact method. First, a multi-area damage mining model, which can describe damages in different spatial layers, is built based on an infrared thermal image sequence. Subsequently, to identify different impact damage types from infrared image data effectively, the inference is used to solve for the parameters in the model. Then, an image-processing framework is proposed to eliminate errors and compare locations of different damage types. It includes an image segmentation algorithm with an energy function and an image fusion method with . In the experiment, the proposed method is used to evaluate the complex damages caused by the impact of the secondary debris cloud on the rear wall of the typical Whipple shield configuration. Experimental results show that it can effectively identify and evaluate the complex damage caused by , including surface and internal defects.

Keywords： Hypervelocity impact     Variational Bayesian     Sparse representation     Damage assessment    

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Title Author Date Type Operation

Evaluation of liquefaction-induced lateral displacement using Bayesian belief networks

Mahmood AHMAD, Xiao-Wei TANG, Jiang-Nan QIU, Feezan AHMAD

Journal Article

A knowledge reasoning Fuzzy-Bayesian network for root cause analysis of abnormal aluminum electrolysis

Weichao Yue, Xiaofang Chen, Weihua Gui, Yongfang Xie, Hongliang Zhang

Journal Article

A case study on sample average approximation method for stochastic supply chain network design problem

Yuan WANG, Ruyan SHOU, Loo Hay LEE, Ek Peng CHEW

Journal Article

A Bayesian modeling approach to bi-directional pedestrian flows in carnival events

S. Q. XIE, S. C. WONG, William H. K. LAM

Journal Article

An assessment of surrogate fuel using Bayesian multiple kernel learning model in sight of sooting tendency

Journal Article

Identification of pollution sources in rivers using a hydrodynamic diffusion wave model and improved Bayesian-Markov

Journal Article

Hybrid Bayesian Network Method for Predicting Intrusion

Wang Liangmin, Ma Jianfeng

Journal Article

Controller area network node reliability assessment based on observable node information

Lei-ming ZHANG, Long-hao TANG, Yong LEI

Journal Article

Quality-related locally weighted soft sensing for non-stationary processes by a supervised Bayesian network

Journal Article

Short-term Load Forecasting Using Neural Network

Luo Mei

Journal Article

Application of machine learning algorithms for the evaluation of seismic soil liquefaction potential

Mahmood AHMAD, Xiao-Wei TANG, Jiang-Nan QIU, Feezan AHMAD, Wen-Jing GU

Journal Article

A novel multimode process monitoring method integrating LDRSKM with Bayesian inference

Shi-jin REN,Yin LIANG,Xiang-jun ZHAO,Mao-yun YANG

Journal Article

A Probabilistic Architecture of Long-Term Vehicle Trajectory Prediction for Autonomous Driving

Jinxin Liu, Yugong Luo, Zhihua Zhong, Keqiang Li, Heye Huang, Hui Xiong

Journal Article

Data-Driven Model Falsification and Uncertainty Quantification for Fractured Reservoirs

Junling Fang, Bin Gong, Jef Caers

Journal Article

Variational Bayesian multi-sparse component extraction for damage reconstruction of space debris hypervelocity

Xuegang HUANG, Anhua SHI, Qing LUO, Jinyang LUO,emei-126@126.com

Journal Article