Ying‐Chun Chang

495 total citations
50 papers, 363 citations indexed

About

Ying‐Chun Chang is a scholar working on Biomedical Engineering, Automotive Engineering and Signal Processing. According to data from OpenAlex, Ying‐Chun Chang has authored 50 papers receiving a total of 363 indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Biomedical Engineering, 13 papers in Automotive Engineering and 13 papers in Signal Processing. Recurrent topics in Ying‐Chun Chang's work include Acoustic Wave Phenomena Research (40 papers), Vehicle Noise and Vibration Control (13 papers) and Speech and Audio Processing (11 papers). Ying‐Chun Chang is often cited by papers focused on Acoustic Wave Phenomena Research (40 papers), Vehicle Noise and Vibration Control (13 papers) and Speech and Audio Processing (11 papers). Ying‐Chun Chang collaborates with scholars based in Taiwan and China. Ying‐Chun Chang's co-authors include Min‐Chie Chiu, Long-Jyi Yeh, Mengru Wu and Cheng‐Chieh Lin and has published in prestigious journals such as The Journal of the Acoustical Society of America, International Journal for Numerical Methods in Engineering and Journal of Sound and Vibration.

In The Last Decade

Ying‐Chun Chang

44 papers receiving 339 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ying‐Chun Chang Taiwan 10 265 110 96 80 62 50 363
Long-Jyi Yeh Taiwan 11 197 0.7× 73 0.7× 60 0.6× 59 0.7× 37 0.6× 45 322
Laurent Gagliardini France 12 341 1.3× 281 2.6× 51 0.5× 174 2.2× 80 1.3× 35 565
K. H. Heron United Kingdom 11 400 1.5× 227 2.1× 92 1.0× 86 1.1× 142 2.3× 22 572
Nilson Barbieri Brazil 14 197 0.7× 250 2.3× 87 0.9× 56 0.7× 167 2.7× 43 623
S.N. Panigrahi India 11 151 0.6× 67 0.6× 64 0.7× 47 0.6× 84 1.4× 19 396
Krzysztof Mazur Poland 11 143 0.5× 91 0.8× 53 0.6× 56 0.7× 88 1.4× 39 389
Kenneth D. Frampton United States 15 303 1.1× 100 0.9× 298 3.1× 25 0.3× 72 1.2× 52 543
Andrew Elliott United Kingdom 11 318 1.2× 230 2.1× 35 0.4× 323 4.0× 24 0.4× 41 490
Weiping Ding China 10 152 0.6× 77 0.7× 60 0.6× 270 3.4× 9 0.1× 34 382
Masaaki OKUMA Japan 10 64 0.2× 167 1.5× 45 0.5× 93 1.2× 62 1.0× 64 322

Countries citing papers authored by Ying‐Chun Chang

Since Specialization
Citations

This map shows the geographic impact of Ying‐Chun Chang'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 Ying‐Chun Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ying‐Chun Chang more than expected).

Fields of papers citing papers by Ying‐Chun Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ying‐Chun Chang. 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 Ying‐Chun Chang. The network helps show where Ying‐Chun Chang may publish in the future.

Co-authorship network of co-authors of Ying‐Chun Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Ying‐Chun Chang. A scholar is included among the top collaborators of Ying‐Chun Chang 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 Ying‐Chun Chang. Ying‐Chun Chang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Chiu, Min‐Chie & Ying‐Chun Chang. (2023). Numerical assessment of gun mufflers using finite element method, neural networks, and a genetic algorithm. Noise & Vibration Worldwide. 54(4-5). 224–234. 1 indexed citations
2.
Chiu, Min‐Chie, et al.. (2022). Optimization of Screw Mufflers Equipped with Two Inlets and One Outlet Using Neural Network Model, Finite Element Method, and Genetic Algorithm. Mathematical Problems in Engineering. 2022. 1–11. 1 indexed citations
3.
Chiu, Min‐Chie & Ying‐Chun Chang. (2022). Acoustical simulation of pneumatic mufflers hybridized with metal sintered bronze porous material, a spiral tube, and expansion cones. Building Acoustics. 29(3). 433–442. 1 indexed citations
4.
Chang, Ying‐Chun, et al.. (2019). Numerical analysis of circular straight mufflers equipped with three chambers at high-order-modes. Applied Acoustics. 155. 167–179. 9 indexed citations
5.
Chiu, Min‐Chie, Ying‐Chun Chang, & Mengru Wu. (2018). Numerical Assessment of Automotive Mufflers Using FEM, Neural Networks, and a Genetic Algorithm. Archives of Acoustics. 517–517. 5 indexed citations
6.
Chiu, Min‐Chie, et al.. (2018). Optimization of a two-mass vibration-based electromagnetic energy harvester using simulated annealing method. Journal of low frequency noise, vibration and active control. 37(1). 90–106. 9 indexed citations
7.
Chang, Ying‐Chun, et al.. (2017). Noise Elimination of Reciprocating Compressors Using FEM, Neural Networks Method, and the GA Method. Archives of Acoustics. 42(2). 189–197. 1 indexed citations
8.
Chiu, Min‐Chie, et al.. (2016). Numerical Assessment of a One-Mass Spring-Based Electromagnetic Energy Harvester on a Vibrating Object. Archives of Acoustics. 41(1). 119–131. 11 indexed citations
9.
Chiu, Min‐Chie & Ying‐Chun Chang. (2015). An Assessment of High-Order-Mode Analysis and Shape Optimization of Expansion Chamber Mufflers. Archives of Acoustics. 39(4). 489–499. 7 indexed citations
10.
Chiu, Min‐Chie, et al.. (2015). An Acoustical Simulation for the Muffler of Reciprocating Compressors Using the FEM Method. Noise & Vibration Worldwide. 46(9). 10–18.
11.
Chiu, Min‐Chie & Ying‐Chun Chang. (2013). Numerical Assessment of Plenums Intersected by Four Baffles Using the Boundary Element Method, Genetic Algorithm, and Neural Networks. Noise & Vibration Worldwide. 44(11). 25–44. 2 indexed citations
12.
Chiu, Min‐Chie, et al.. (2013). A study of the measurement system capability for a gauge block comparator. Journal of Interdisciplinary Mathematics. 16(4-5). 245–286. 1 indexed citations
13.
14.
Chang, Ying‐Chun, et al.. (2010). SHAPE OPTIMIZATION OF ONE-CHAMBER MUFFLERS WITH PERFORATED INTRUDING TUBES USING A SIMULATED ANNEALING METHOD. Journal of marine science and technology. 18(4). 3 indexed citations
15.
Chang, Ying‐Chun. (2008). Numerical Optimization of Single-chamber Mufflers Using Neural Networks and Genetic Algorithm. TURKISH JOURNAL OF ENGINEERING AND ENVIRONMENTAL SCIENCES. 32(6). 313–322. 2 indexed citations
16.
Chiu, Min‐Chie, et al.. (2007). OPTIMIZATION OF PERFORATED DOUBLELAYER ABSORBERS USING SIMULATED ANNEALING. Journal of marine science and technology. 15(4). 4 indexed citations
17.
Yeh, Long-Jyi, Ying‐Chun Chang, & Min‐Chie Chiu. (2005). Numerical studies on constrained venting system with reactive mufflers by GA optimization. International Journal for Numerical Methods in Engineering. 65(8). 1165–1185. 30 indexed citations
18.
Chang, Ying‐Chun, et al.. (2004). Computer Aided Design on Single Expansion Muffler with Extended Tube under Space Constraints. Journal of Applied Science and Engineering. 7(3). 171–181. 12 indexed citations
19.
Yeh, Long-Jyi, et al.. (2004). GA optimization on multi-segments muffler under space constraints. Applied Acoustics. 65(5). 521–543. 31 indexed citations
20.
Chang, Ying‐Chun, Long-Jyi Yeh, & Min‐Chie Chiu. (2004). Optimization of double‐layer absorbers on constrained sound absorption system by using genetic algorithm. International Journal for Numerical Methods in Engineering. 62(3). 317–333. 13 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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2026