D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 33 Citations 5,957 290 World Ranking 4214 National Ranking 293

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Artificial intelligence
  • Mechanical engineering

His main research concerns Fuzzy logic, Mathematical optimization, Reliability, Data mining and Probabilistic logic. In his study, which falls under the umbrella issue of Fuzzy logic, Randomness, Interval and Uncertainty quantification is strongly linked to Imprecise probability. His Mathematical optimization research includes elements of Algorithm, Finite element method and Probability distribution.

The Reliability study combines topics in areas such as Upper and lower bounds and Operations research. His Data mining study integrates concerns from other disciplines, such as Fuzzy set operations, Fuzzy classification and Fuzzy measure theory. His work on Probabilistic method is typically connected to Sea state as part of general Probabilistic logic study, connecting several disciplines of science.

His most cited work include:

  • Fuzzy Randomness: Uncertainty in Civil Engineering and Computational Mechanics (315 citations)
  • Imprecise probabilities in engineering analyses (232 citations)
  • Fuzzy structural analysis using α-level optimization (205 citations)

What are the main themes of his work throughout his whole career to date?

Michael Beer focuses on Reliability, Mathematical optimization, Uncertainty quantification, Algorithm and Applied mathematics. His biological study spans a wide range of topics, including Complex system, Reliability engineering and Structural engineering. His Mathematical optimization research incorporates themes from Stochastic process, Optimal design, Random variable and Fuzzy logic.

The concepts of his Uncertainty quantification study are interwoven with issues in Bayesian inference, Imprecise probability, Probabilistic logic, Interval and Monte Carlo method. Michael Beer has researched Algorithm in several fields, including Bhattacharyya distance, Statistical model, Kriging and Sensitivity. His Applied mathematics research focuses on Nonlinear system and how it connects with Response spectrum.

He most often published in these fields:

  • Reliability (45.06%)
  • Mathematical optimization (46.27%)
  • Uncertainty quantification (47.23%)

What were the highlights of his more recent work (between 2019-2021)?

  • Uncertainty quantification (47.23%)
  • Reliability (45.06%)
  • Random variable (31.33%)

In recent papers he was focusing on the following fields of study:

Michael Beer mainly investigates Uncertainty quantification, Reliability, Random variable, Mathematical optimization and Applied mathematics. Michael Beer has included themes like Finite element method, Bayesian inference, Imprecise probability, Probabilistic logic and Realization in his Uncertainty quantification study. As a member of one scientific family, Michael Beer mostly works in the field of Reliability, focusing on Reliability engineering and, on occasion, Mechanism and Measure.

The study incorporates disciplines such as Stochastic process, Probability density function and Class in addition to Random variable. Michael Beer incorporates Mathematical optimization and Context in his research. His Applied mathematics research includes themes of Maxima and minima, Operator norm, Polynomial chaos, Upper and lower bounds and Propagation of uncertainty.

Between 2019 and 2021, his most popular works were:

  • Reliability and importance analysis of uncertain system with common cause failures based on survival signature (16 citations)
  • Reliability and importance analysis of uncertain system with common cause failures based on survival signature (16 citations)
  • Reliability and importance analysis of uncertain system with common cause failures based on survival signature (16 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Artificial intelligence
  • Mechanical engineering

Uncertainty quantification, Algorithm, Bayesian inference, Stochastic simulation and Imprecise probability are his primary areas of study. His Uncertainty quantification research integrates issues from Operator norm, Importance sampling, Applied mathematics and Mechanism. His Algorithm research is multidisciplinary, relying on both Failure mode and effects analysis, Bayesian network and Plot.

His study in Bayesian inference is interdisciplinary in nature, drawing from both Complex system, Probabilistic logic, Reliability engineering and Measure. His Stochastic simulation study incorporates themes from Estimator and Rare events. His research investigates the connection with Estimator and areas like Sensitivity which intersect with concerns in Probability density function, Random variable, Mathematical optimization and Probability measure.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Fuzzy Randomness: Uncertainty in Civil Engineering and Computational Mechanics

Bernd Möller;Michael Beer.
(2004)

688 Citations

Imprecise probabilities in engineering analyses

Michael Beer;Scott Ferson;Vladik Y Kreinovich.
Mechanical Systems and Signal Processing (2013)

366 Citations

Fuzzy structural analysis using α-level optimization

B. Möller;W. Graf;M. Beer.
Computational Mechanics (2000)

345 Citations

Engineering computation under uncertainty - Capabilities of non-traditional models

Bernd Möller;Michael Beer.
Computers & Structures (2008)

325 Citations

Safety assessment of structures in view of fuzzy randomness

Bernd Möller;Wolfgang Graf;Michael Beer.
Computers & Structures (2003)

206 Citations

Advanced line sampling for efficient robust reliability analysis

Marco de Angelis;Edoardo Patelli;Michael Beer.
Structural Safety (2015)

153 Citations

Reliability analysis with scarce information: Comparing alternative approaches in a geotechnical engineering context

Michael Beer;Yi Zhang;Ser Tong Quek;Kok Kwang Phoon.
Structural Safety (2013)

147 Citations

Ecology of the Microbial Community Removing Phosphate from Wastewater under Continuously Aerobic Conditions in a Sequencing Batch Reactor

Johwan Ahn;Sarah Schroeder;Michael Beer;Simon McIlroy.
Applied and Environmental Microbiology (2007)

133 Citations

Structural reliability analysis on the basis of small samples: An interval quasi-Monte Carlo method

Hao Zhang;Hongzhe Dai;Michael Beer;Wei Wang.
Mechanical Systems and Signal Processing (2013)

123 Citations

Phylogeny of the filamentous bacterium Eikelboom Type 1851, and design and application of a 16S rRNA targeted oligonucleotide probe for its fluorescence in situ identification in activated sludge

Michael Beer;Elizabeth M Seviour;Yun Kong;Mitchell Cunningham.
Fems Microbiology Letters (2002)

119 Citations

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