Jia‐Hua Yang

821 total citations
27 papers, 640 citations indexed

About

Jia‐Hua Yang is a scholar working on Civil and Structural Engineering, Statistics, Probability and Uncertainty and Mechanics of Materials. According to data from OpenAlex, Jia‐Hua Yang has authored 27 papers receiving a total of 640 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Civil and Structural Engineering, 9 papers in Statistics, Probability and Uncertainty and 5 papers in Mechanics of Materials. Recurrent topics in Jia‐Hua Yang's work include Structural Health Monitoring Techniques (25 papers), Infrastructure Maintenance and Monitoring (16 papers) and Probabilistic and Robust Engineering Design (9 papers). Jia‐Hua Yang is often cited by papers focused on Structural Health Monitoring Techniques (25 papers), Infrastructure Maintenance and Monitoring (16 papers) and Probabilistic and Robust Engineering Design (9 papers). Jia‐Hua Yang collaborates with scholars based in Hong Kong, China and United Kingdom. Jia‐Hua Yang's co-authors include Heung‐Fai Lam, Siu‐Kui Au, Jun Hu, Yanping Yang, James L. Beck, Haibei Xiong, Feng‐Liang Zhang, Yonghui An, Qin Hu and Linxin Peng and has published in prestigious journals such as Mechanical Systems and Signal Processing, Engineering Structures and Biochemical Society Transactions.

In The Last Decade

Jia‐Hua Yang

27 papers receiving 623 citations

Peers

Jia‐Hua Yang

CSE

SPU

CSE

Ellen Simoen Belgium

Yan‐Chun Ni China

Giorgio Barone United Kingdom

Bijaya Jaishi China

Giuseppe Abbiati Denmark

Omid Sedehi Hong Kong

Yu Xin China

Michael W. Vanik United States

Seyed Rohollah Hoseini Vaez Iran

Martin Dalgaard Ulriksen Denmark

Ellen Simoen Belgium

Jia‐Hua Yang

513 ×0.9

CSE

279 ×1.3

SPU

91 ×0.7

73 ×0.7

49 ×0.8

CSE

Citations per year, relative to Jia‐Hua Yang Jia‐Hua Yang (= 1×) peers Ellen Simoen

Countries citing papers authored by Jia‐Hua Yang

Since Specialization

Citations

This map shows the geographic impact of Jia‐Hua Yang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jia‐Hua Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jia‐Hua Yang more than expected).

Fields of papers citing papers by Jia‐Hua Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jia‐Hua Yang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jia‐Hua Yang. The network helps show where Jia‐Hua Yang may publish in the future.

Co-authorship network of co-authors of Jia‐Hua Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Jia‐Hua Yang. A scholar is included among the top collaborators of Jia‐Hua Yang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jia‐Hua Yang. Jia‐Hua Yang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Yang, Jia‐Hua, et al.. (2025). Development of an adaptive model class for considering spatiotemporal correlation in Bayesian model updating and system identification. Engineering Structures. 333. 120046–120046. 1 indexed citations

Hu, Qin, et al.. (2025). Brace damage identification of a transmission tower via a sparse Bayesian learning method with variational inference and enhanced PSO algorithm. Structures. 77. 109170–109170. 2 indexed citations

Yang, Jia‐Hua, Shengguo Zhao, & Bo Lin. (2024). Effect of commercial fibrolytic enzymes application to normal- and slightly lower energy diets on lactational performance, digestibility and plasma nutrients in high-producing dairy cows. Frontiers in Veterinary Science. 11. 1302034–1302034. 3 indexed citations

Zhang, Feng‐Liang, et al.. (2024). Bayesian model updating of a 250 m super-tall building utilizing an enhanced Markov chain Monte Carlo simulation algorithm. Case Studies in Construction Materials. 21. e03650–e03650. 1 indexed citations

Yang, Jia‐Hua, Wenyue Liu, Yonghui An, & Heung‐Fai Lam. (2023). Enhanced adaptive sequential Monte Carlo method for Bayesian model class selection by quantifying data fit and information gain. Mechanical Systems and Signal Processing. 206. 110792–110792. 6 indexed citations

Yang, Jia‐Hua, et al.. (2023). A Markov chain Monte Carlo-based Bayesian framework for system identification and uncertainty estimation of full-scale structures. Engineering Structures. 295. 116886–116886. 8 indexed citations

Lam, Heung‐Fai & Jia‐Hua Yang. (2022). Vibration Testing and Applications in System Identification of Civil Engineering Structures. 5 indexed citations

Yang, Jia‐Hua, Heung‐Fai Lam, & Yonghui An. (2022). Development of a two-phase adaptive MCMC method for efficient Bayesian model updating of complex dynamic systems. Engineering Structures. 270. 114836–114836. 22 indexed citations

Yang, Jia‐Hua, Qingzhao Kong, Hongjun Liu, & H.Y. Peng. (2021). Efficient Bayesian model class selection of vector autoregressive models for system identification. Structural Control and Health Monitoring. 28(9). 5 indexed citations

10.

Yang, Jia‐Hua, et al.. (2019). Structural modal identification and MCMC-based model updating by a Bayesian approach. Smart Structures and Systems. 24(5). 631. 1 indexed citations

11.

Zhang, Feng‐Liang, et al.. (2019). Structural health monitoring of a 250‐m super‐tall building and operational modal analysis using the fast Bayesian FFT method. Structural Control and Health Monitoring. e2383–e2383. 45 indexed citations

12.

Lam, Heung‐Fai, Jia‐Hua Yang, & James L. Beck. (2019). Bayesian operational modal analysis and assessment of a full-scale coupled structural system using the Bayes-Mode-ID method. Engineering Structures. 186. 183–202. 14 indexed citations

13.

Yang, Jia‐Hua, Heung‐Fai Lam, & James L. Beck. (2019). Bayes-Mode-ID: A Bayesian modal-component-sampling method for operational modal analysis. Engineering Structures. 189. 222–240. 14 indexed citations

14.

Yang, Jia‐Hua & Heung‐Fai Lam. (2018). An efficient adaptive sequential Monte Carlo method for Bayesian model updating and damage detection. Structural Control and Health Monitoring. 25(12). e2260–e2260. 32 indexed citations

15.

Hu, Jun & Jia‐Hua Yang. (2018). Operational Modal Analysis and Bayesian Model Updating of a Coupled Building. International Journal of Structural Stability and Dynamics. 19(1). 1940012–1940012. 15 indexed citations

16.

Lam, Heung‐Fai, et al.. (2017). Identification of rail-sleeper-ballast system through time-domain Markov chain Monte Carlo-based Bayesian approach. Engineering Structures. 140. 421–436. 36 indexed citations

17.

Hu, Jun, Heung‐Fai Lam, & Jia‐Hua Yang. (2017). Operational modal identification and finite element model updating of a coupled building following Bayesian approach. Structural Control and Health Monitoring. 25(2). e2089–e2089. 28 indexed citations

18.

Yang, Jia‐Hua. (2015). Development of Bayesian structural damage detection methodologies utilizing advanced Monte Carlo simulation. 6 indexed citations

19.

Lam, Heung‐Fai, Qin Hu, & Jia‐Hua Yang. (2011). Crack Detection of Thin Plate Structures Utilizing Measured Vibration. Procedia Engineering. 14. 1524–1532. 3 indexed citations

20.

Yang, Jia‐Hua, et al.. (2005). Metabolic flux distribution analysis by 13C-tracer experiments using the Markov chain–Monte Carlo method. Biochemical Society Transactions. 33(6). 1421–1421. 5 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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