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 37 Citations 5,373 117 World Ranking 3046 National Ranking 308

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Artificial intelligence
  • Machine learning

His primary areas of investigation include Bayesian probability, Algorithm, Modal, System identification and Probabilistic logic. His Bayesian probability study is concerned with Statistics in general. He has included themes like Bayes' theorem and Identification in his Algorithm study.

His Modal research integrates issues from Normal mode, Spectral density, Structural engineering, Structural health monitoring and Modal analysis. His System identification study combines topics in areas such as Ambient vibration, Mathematical optimization and Joint probability distribution. His Probabilistic logic research includes themes of Reliability, Slope stability analysis and Model selection.

His most cited work include:

  • Model Selection using Response Measurements: Bayesian Probabilistic Approach (414 citations)
  • Bayesian Methods for Structural Dynamics and Civil Engineering (268 citations)
  • Efficient model updating and health monitoring methodology using incomplete modal data without mode matching (122 citations)

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

His primary scientific interests are in Bayesian inference, Bayesian probability, Algorithm, Artificial intelligence and Probabilistic logic. The concepts of his Bayesian inference study are interwoven with issues in Markov chain Monte Carlo, Uncertainty quantification, Selection, Model selection and Structural health monitoring. His Bayesian probability study integrates concerns from other disciplines, such as Artificial neural network and Air quality index.

His Algorithm study combines topics from a wide range of disciplines, such as Modal, Kalman filter, Extended Kalman filter, Noise and System identification. His Artificial intelligence research is multidisciplinary, incorporating elements of Nonparametric statistics, Machine learning, Computer vision and Pattern recognition. The various areas that Ka-Veng Yuen examines in his Probabilistic logic study include Reliability, Geotechnical engineering, Probability density function and Linear system.

He most often published in these fields:

  • Bayesian inference (24.04%)
  • Bayesian probability (24.59%)
  • Algorithm (22.95%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (19.67%)
  • Structural health monitoring (15.85%)
  • Bayesian inference (24.04%)

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

Ka-Veng Yuen mainly investigates Artificial intelligence, Structural health monitoring, Bayesian inference, Data mining and Identification. His Artificial intelligence research focuses on Machine learning and how it relates to Nonparametric statistics. The study incorporates disciplines such as Econometrics and Multi resolution in addition to Structural health monitoring.

His Bayesian inference study incorporates themes from Markov chain Monte Carlo, Reliability engineering, Probabilistic logic, Reliability and Feature selection. His research in Data mining intersects with topics in Modal data, Pairwise comparison and Bayesian probability. His work in Bayesian probability addresses subjects such as Algorithm, which are connected to disciplines such as Inverse problem.

Between 2018 and 2021, his most popular works were:

  • A Review of Point Set Registration: From Pairwise Registration to Groupwise Registration. (26 citations)
  • A closed-form solution for column-supported embankments with geosynthetic reinforcement (18 citations)
  • Self‐calibrating Bayesian real‐time system identification (13 citations)

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

  • Statistics
  • Artificial intelligence
  • Machine learning

Ka-Veng Yuen mainly focuses on Structural health monitoring, Geotechnical engineering, Data mining, Nonparametric statistics and Excavation. Ka-Veng Yuen has researched Structural health monitoring in several fields, including Data stream, Dynamical systems theory, Econometrics and Artificial intelligence. His studies in Artificial intelligence integrate themes in fields like Machine learning and Damage detection.

Identification is often connected to Bayesian probability in his work. His Bayesian probability study combines topics from a wide range of disciplines, such as Uncertainty quantification and Kriging. Ka-Veng Yuen has included themes like Algorithm and Bayesian inference in his Markov chain Monte Carlo study.

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

Model Selection using Response Measurements: Bayesian Probabilistic Approach

James L. Beck;Ka-Veng Yuen.
Journal of Engineering Mechanics-asce (2004)

568 Citations

Bayesian Methods for Structural Dynamics and Civil Engineering

Ka-Veng Yuen.
(2010)

475 Citations

Overview of Environment Perception for Intelligent Vehicles

Hao Zhu;Ka-Veng Yuen;Lyudmila Mihaylova;Henry Leung.
IEEE Transactions on Intelligent Transportation Systems (2017)

182 Citations

Bayesian spectral density approach for modal updating using ambient data

Lambros S. Katafygiotis;Ka-Veng Yuen.
Earthquake Engineering & Structural Dynamics (2001)

173 Citations

Efficient model updating and health monitoring methodology using incomplete modal data without mode matching

Ka-Veng Yuen;James L. Beck;Lambros S. Katafygiotis.
Structural Control & Health Monitoring (2006)

168 Citations

Two-Stage Structural Health Monitoring Approach for Phase I Benchmark Studies

Ka-Veng Yuen;Siu Kui Au;James L. Beck.
Journal of Engineering Mechanics-asce (2004)

146 Citations

Recent developments of Bayesian model class selection and applications in civil engineering

Ka-Veng Yuen.
Structural Safety (2010)

142 Citations

Bayesian Fast Fourier Transform Approach for Modal Updating Using Ambient Data

Ka-Veng Yuen;Lambros S. Katafygiotis.
Advances in Structural Engineering (2003)

137 Citations

Bayesian Methods for Updating Dynamic Models

Ka-Veng Yuen;Sin-Chi Kuok.
Applied Mechanics Reviews (2011)

134 Citations

Ambient interference in long-term monitoring of buildings

Ka-Veng Yuen;Sin-Chi Kuok.
Engineering Structures (2010)

123 Citations

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