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Heuristic-Based Recommendation System for Dealing With Abnormal Situations in Industrial Applications

Márcio J. da Silva, Carlos E. Pereira

Publisher: ASME

ASME J. Risk Uncertainty Part B. June 2025, 11(2): 021104.

Paper No: RISK-24-1089

https://doi.org/10.1115/1.4067827

Published Online: February 28, 2025

... 01 2025 28 02 2025 probabilistic ontology industrial alarm system decision under uncertainty multi-entity Bayesian network The technological evolution of automation systems has enabled an exponential growth of process data acquisition in those systems. Despite all the efforts...

View Articletitled, Heuristic-Based Recommendation System for Dealing With Abnormal Situations in Industrial Applications

Topics: Bayesian network, Data mining, Decision making, Failure, Machinery, Modeling, Ontologies, Probability, Semantics, Trains

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering

Extreme Wind Speed Map for Mainland China Considering the Directional Effect

Xu Hong; Tianle Chen; Sheng Wang; Fan Kong; Maofang Liu

Robust Optimum Design for Hybrid Vibration Control of Structures under Multihazard Scenarios of Earthquakes and Winds

Sarranya Banerjee; Taiki Saito; Vasant Matsagar

System Reliability–Based Disaster Resilience Analysis of Cable-Stayed Bridge under Tank Truck Fire Hazards

Seonghyun Lim; Sang-ri Yi; Hyunjoong Kim; Junho Song

Gaussian Process Regression–Based Model Error Diagnosis and Quantification Using Experimental Data of Prestressed Concrete Beams in Shear

Jiadaren Liu; John Alexander; Yong Li

Decomposition of the Hierarchical Variability of Concrete Random Fields and Its Influence on the Hysteretic Behavior of Structural Components

Jinju Tao, Ph.D.; Sicheng Ren; Beibei Xiong, Ph.D.

Robustness of Urban Rail Transit Networks Considering Cascade Failure under Attacks: A Case Study of Nanjing, China

Zhuanglin Ma; Dawei Hu; Steven I-Jy Chien; Jie Liu; Yue Liu; Ke Wu

Identification of Causes and Individuals at Risk of Falls during Vertical Formwork Operation in Construction

Vigneshkumar Chellappa, Ph.D.; Urmi Ravindra Salve, Ph.D.

Performance-Based Risk Assessment for Large-Scale Transportation Networks Using the Transitional Markov Chain Monte Carlo Method

Anteneh Z. Deriba; David Y. Yang, Ph.D.

Multilevel Damage Indicator–Enabled Seismic Damage Evolution Analysis and Fragility Assessment of Structures

Yi-Zheng Xu; Zi-Xuan Gui; Xu-Yang Cao, Ph.D.; De-Cheng Feng, Ph.D.

Improved Probabilistic Seismic Demand–Intensity Relationship: Heteroscedastic Approaches

Libo Chen

Quantitative Analysis of Risk Influential Factors of Evacuation Accidents for Passenger Ships

Zhongyuan Liu; Xinjian Wang; Wenjie Cao; Jiashi Wang; Siming Fang; Sean Loughney

Advance Rate Predictions of Tunnel Boring Machines Using Bayesian-Optimized CNN-LSTM

Xiaoxiong Men; Yuanfei Li; Baohe Guo; Lai Wang; Xinyu Ye; Qiujing Pan

Reliability of Steel Girder Bridges Subjected to Blast Loads

Ahmad Alsendi, Ph.D.; Christopher D. Eamon

Analysis of Deformation Characteristics of Layered Rock Tunnel Excavation Based on Statistical Mechanics of Rock Masses

Faquan Wu; Weixin Wan; Yun Tian; Ying Yang; Bing Yang

Probabilistic Analysis of Performance of Three-Dimensional Supported Excavations Considering Soil Spatial Variability

Liang Zhang; Hamed Dehghanpour; Jiajie Cheng; Lei Wang

Active Learning of Small Failure Probabilities of Highly Nonstationary Geotechnical Systems by Adaptive Bayesian Compressive Sensing and Subset Simulation

Peiping Li

Interpolation of Sparse Measurements and Quantification of Measurement Error Using Enhanced Kriging with Sparse Representation of Covariance Function

Cong Miao; Yu Wang

Adaptive Monte Carlo Methods for Estimating Rare Events in Power Grids

Jianpeng Chan; Roger Paredes; Iason Papaioannou; Leonardo Duenas-Osorio; Daniel Straub

Health Evaluation of Frame Structures Based on the Gray Cloud Network Model: Proposal and Experimental Study

Kaixuan Zheng; Huiyong Guo; Jin Di; Chen Liu

Smart Heuristics in Civil Engineering: Unearthing the Unexploited

Peter E. D. Love, Ph.D.

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