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Michael Beer
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2020 – today
- 2024
- [j37]Yan Shi, Michael Beer
:
Physics-informed neural network classification framework for reliability analysis. Expert Syst. Appl. 258: 125207 (2024) - [j36]Wentao Mao
Tensor representation-based transferability analytics and selective transfer learning of prognostic knowledge for remaining useful life prediction across machines. Reliab. Eng. Syst. Saf. 242: 109695 (2024) - [j35]Danko J. Jerez
Optimal borehole placement for the design of rectangular shallow foundation systems under undrained soil conditions: A stochastic framework. Reliab. Eng. Syst. Saf. 242: 109771 (2024) - [j34]Yan Shi, Jasper Behrensdorf
Network reliability analysis through survival signature and machine learning techniques. Reliab. Eng. Syst. Saf. 242: 109806 (2024) - [j33]Fangqi Hong, Pengfei Wei
A sequential sampling-based Bayesian numerical method for reliability-based design optimization. Reliab. Eng. Syst. Saf. 244: 109939 (2024) - [j32]Lei Wang, Zhuo Hu, Chao Dang
Refined parallel adaptive Bayesian quadrature for estimating small failure probabilities. Reliab. Eng. Syst. Saf. 244: 109953 (2024) - [j31]Youbao Jiang, Xuyang Zhang
An efficient method for reliability-based design optimization of structures under random excitation by mapping between reliability and operator norm. Reliab. Eng. Syst. Saf. 245: 109972 (2024) - [j30]Chao Dang
Semi-Bayesian active learning quadrature for estimating extremely low failure probabilities. Reliab. Eng. Syst. Saf. 246: 110052 (2024) - [j29]Chao Dang
Bayesian active learning line sampling with log-normal process for rare-event probability estimation. Reliab. Eng. Syst. Saf. 246: 110053 (2024) - [j28]Lechang Yang
Reliability evaluation of a multi-state system with dependent components and imprecise parameters: A structural reliability treatment. Reliab. Eng. Syst. Saf. 250: 110240 (2024) - [j27]Chen Ding
Sampling and active learning methods for network reliability estimation using K-terminal spanning tree. Reliab. Eng. Syst. Saf. 250: 110309 (2024) - [i4]Jan Grashorn
Transport Map Coupling Filter for State-Parameter Estimation. CoRR abs/2407.02198 (2024) - [i3]Chen Ding, Pengfei Wei, Yan Shi, Jinxing Liu, Matteo Broggi, Michael Beer:
Sampling and active learning methods for network reliability estimation using K-terminal spanning tree. CoRR abs/2407.11053 (2024) - [i2]Wang-Ji Yan, Lin-Feng Mei, Jiang Mo, Costas Papadimitriou, Ka-Veng Yuen, Michael Beer:
Navigating Uncertainties in Machine Learning for Structural Dynamics: A Comprehensive Review of Probabilistic and Non-Probabilistic Approaches in Forward and Inverse Problems. CoRR abs/2408.08629 (2024) - 2023
- [j26]Kang Liao, Yiping Wu
Probabilistic risk assessment of earth dams with spatially variable soil properties using random adaptive finite element limit analysis. Eng. Comput. 39(5): 3313-3326 (2023) - [j25]Xiukai Yuan
Global failure probability function estimation based on an adaptive strategy and combination algorithm. Reliab. Eng. Syst. Saf. 231: 108937 (2023) - [j24]Yang Zhang
A single-loop time-variant reliability evaluation via a decoupling strategy and probability distribution reconstruction. Reliab. Eng. Syst. Saf. 232: 109031 (2023) - [j23]Kun Zhang, Ning Chen, Jian Liu, Shaohui Yin, Michael Beer
An efficient meta-model-based method for uncertainty propagation problems involving non-parameterized probability-boxes. Reliab. Eng. Syst. Saf. 238: 109477 (2023) - [c17]Jasper Behrensdorf
Imprecise Survival Signature Approximation Using Interval Predictor Models. SSCI 2023: 506-511 - [p1]Oscar Galindo, Christopher Ibarra, Vladik Kreinovich, Michael Beer
Fourier Transform and Other Quadratic Problems Under Interval Uncertainty. Decision Making Under Uncertainty and Constraints 2023: 251-256 - 2022
- [j22]Jia-Shu Yang
An efficient approach for dynamic-reliability-based topology optimization of braced frame structures with probability density evolution method. Adv. Eng. Softw. 173: 103196 (2022) - [j21]Caroline Morais, Hector Diego Estrada-Lugo
Robust data-driven human reliability analysis using credal networks. Reliab. Eng. Syst. Saf. 218(Part): 107990 (2022) - [j20]Chao Dang
Parallel adaptive Bayesian quadrature for rare event estimation. Reliab. Eng. Syst. Saf. 225: 108621 (2022) - [j19]Danko J. Jerez
An effective implementation of reliability methods for Bayesian model updating of structural dynamic models with multiple uncertain parameters. Reliab. Eng. Syst. Saf. 225: 108634 (2022) - [j18]Kun Zhang, Ning Chen, Peng Zeng, Jian Liu, Michael Beer
An efficient reliability analysis method for structures with hybrid time-dependent uncertainty. Reliab. Eng. Syst. Saf. 228: 108794 (2022) - 2021
- [j17]Matthias G. R. Faes
Augmented reliability analysis for estimating imprecise first excursion probabilities in stochastic linear dynamics. Adv. Eng. Softw. 155: 102993 (2021) - [j16]Xiukai Yuan
Decoupled reliability-based optimization using Markov chain Monte Carlo in augmented space. Adv. Eng. Softw. 157-158: 103020 (2021) - [j15]Lechang Yang
Reliability analysis of a complex system with hybrid structures and multi-level dependent life metrics. Reliab. Eng. Syst. Saf. 209: 107469 (2021) - [j14]Xiukai Yuan
Efficient imprecise reliability analysis using the Augmented Space Integral. Reliab. Eng. Syst. Saf. 210: 107477 (2021) - [j13]Marcos A. Valdebenito
Failure probability estimation of a class of series systems by multidomain Line Sampling. Reliab. Eng. Syst. Saf. 213: 107673 (2021) - [j12]Jasper Behrensdorf
Numerically efficient computation of the survival signature for the reliability analysis of large networks. Reliab. Eng. Syst. Saf. 216: 107935 (2021) - [j11]Julian Salomon
Efficient reliability analysis of complex systems in consideration of imprecision. Reliab. Eng. Syst. Saf. 216: 107972 (2021) - [c16]Michael Beer
Uncertainty: Ideas Behind Neural Networks Lead Us Beyond KL- Decomposition and Interval Fields. SSCI 2021: 1-7 - 2020
- [j10]Jinhua Mi, Michael Beer
Reliability and importance analysis of uncertain system with common cause failures based on survival signature. Reliab. Eng. Syst. Saf. 201: 106988 (2020) - [c15]Michael Beer
Why Spiking Neural Networks Are Efficient: A Theorem. IPMU (1) 2020: 59-69 - [c14]Michael Beer
Which Distributions (or Families of Distributions) Best Represent Interval Uncertainty: Case of Permutation-Invariant Criteria. IPMU (1) 2020: 70-79 - [i1]Marco de Angelis, Marco Behrendt
Forward interval propagation through the Fourier discrete transform. CoRR abs/2012.09778 (2020)
2010 – 2019
- 2019
- [j9]Yi Zhang
Reliability analysis with consideration of asymmetrically dependent variables: Discussion and application to geotechnical examples. Reliab. Eng. Syst. Saf. 185: 261-277 (2019) - [c13]Longxue He, Michael Beer
Sensitivity analysis of prior beliefs in advanced Bayesian networks. SSCI 2019: 776-783 - [c12]Marco Behrendt
Development of a Relaxed Stationary Power Spectrum using Imprecise Probabilities with Application to High-rise Buildings. SSCI 2019: 784-790 - 2018
- [j8]Silvia Tolo
An open toolbox for the reduction, inference computation and sensitivity analysis of Credal Networks. Adv. Eng. Softw. 115: 126-148 (2018) - [c11]Michael Beer
What If We Do Not Know Correlations? ECONVN 2018: 78-85 - [c10]Tobias-Emanuel Regenhardt, Md Samdani Azad
A Novel Application of System Survival Signature in Reliability Assessment of Offshore Structures. ICO 2018: 11-20 - 2017
- [c9]Michael Beer
How Accurate Are Expert Estimations of Correlation? SSCI 2017: 1-9 - [c8]Matteo Broggi
Comparison of Bayesian and interval uncertainty quantification: Application to the AIRMOD test structure. SSCI 2017: 1-8 - [c7]Liam A. Comerford, Michael Beer
Revealing prediction uncertainty in artificial neural network based reconstruction of missing data in stochastic process records utilizing extreme learning machines. SSCI 2017: 1-7 - 2016
- [j7]Geng Feng, Edoardo Patelli
Imprecise system reliability and component importance based on survival signature. Reliab. Eng. Syst. Saf. 150: 116-125 (2016) - 2015
- [j6]Yiannis Tsompanakis, Peter Iványi, André Teófilo Beck
Special Issue: Civil-Comp. Adv. Eng. Softw. 89: 1-2 (2015) - [c6]Yuanjin Zhang, Liam A. Comerford, Michael Beer
Compressive sensing for power spectrum estimation of multi-dimensional processes under missing data. IWSSIP 2015: 162-165 - [c5]Raphael Moura
A Clustering Approach to a Major-Accident Data Set: Analysis of Key Interactions to Minimise Human Errors. SSCI 2015: 1838-1843 - 2014
- [c4]Liam A. Comerford, Michael Beer
Compressive sensing based power spectrum estimation from incomplete records by utilizing an adaptive basis. CIES 2014: 117-124 - 2013
- [j5]Matthias Stein, Michael Beer
Bayesian approach for inconsistent information. Inf. Sci. 245: 96-111 (2013) - [j4]Michael Beer
Interval or moments: which carry more information? Soft Comput. 17(8): 1319-1327 (2013) - [j3]Gabor Rebner, Michael Beer
Verified stochastic methods. Soft Comput. 17(8): 1415-1423 (2013) - [c3]Liam A. Comerford, Ioannis A. Kougioumtzoglou, Michael Beer
An artificial neural network based approach for power spectrum estimation and simulation of stochastic processes subject to missing data. CIES 2013: 118-124 - 2012
- [c2]Gabor Rebner, Michael Beer
CUDA Accelerated Fault Tree Analysis with C-XSC. SUM 2012: 539-549 - 2011
- [j2]Rudolf Kruse, Michael Beer
Introduction. Integr. Comput. Aided Eng. 18(3): 201-202 (2011) - 2010
- [c1]Michael Beer
A Summary on Fuzzy Probability Theory. GrC 2010: 5-6
2000 – 2009
- 2009
- [r1]Michael Beer:
Fuzzy Probability Theory. Encyclopedia of Complexity and Systems Science 2009: 4047-4059 - 2003
- [j1]Michael Beer:
Why Total Quality Management Programs Do Not Persist: The Role of Management Quality and Implications for Leading a TQM Transformation. Decis. Sci. 34(4): 623-642 (2003)
Coauthor Index
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