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Pei-Chann Chang

Pei-Chann Chang

Yuan Ze University
Taiwan

D-Index & Metrics

Computer Science

D-Index
60
Citations
9934
World Ranking
3306
National Ranking
21

Pei-Chann Chang publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Pei-Chann Chang sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 240 publications — 59th percentile

59% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Pei-Chann Chang D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Pei-Chann Chang sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 60 D-Index — 78th percentile

78% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Pei-Chann Chang is affiliated with Yuan Ze University in Taiwan and has contributed research primarily in the fields of Engineering and Social Sciences. Their work spans several subfields including Media Technology, Cardiology and Cardiovascular Medicine, Biomedical Engineering, Signal Processing, and Atmospheric Science.

The scientist's recent publications demonstrate a focus on both technical and interdisciplinary topics. Key papers include:

  • A Dual-Adaptive Approach Based on Discrete Cosine Transform for Removal of ECG Baseline Wander, 2022, Applied Sciences
  • Hyperspectral Image Classification Based on the Lightweight G-GhostNets Network, 2025, Acta Interdisciplinary Science
  • The Economic Impact of Major Sporting Events: A Cost-Benefit Analysis of Hosting the Olympic Games, 2025, Frontiers in Business Economics and Management

These works reflect a blend of expertise in biomedical signal processing, remote sensing image classification, and economic analysis related to large-scale sporting events.

The research topics covered by Pei-Chann Chang include:

  • ECG Monitoring and Analysis
  • Analog and Mixed-Signal Circuit Design
  • Digital Filter Design and Implementation
  • Remote-Sensing Image Classification
  • Remote Sensing and Land Use
  • Advanced Image Fusion Techniques
  • Sport and Mega-Event Impacts

Collaborative efforts are evident through coauthorship with researchers such as Jyun-Jie Lin, Ping-Heng Tsai, Farid Uddin Ahmed, and Isabelle Houlbert, each contributing to at least one joint publication.

Pei-Chann Chang's work has been published in a variety of venues, which include:

  • Applied Sciences
  • Acta Interdisciplinary Science
  • Frontiers in Business Economics and Management

The diversity of these publication venues signals an interdisciplinary approach, integrating engineering principles with social science perspectives, particularly in areas like media technology and economic impact assessments.

Best Publications

  • A TSK type fuzzy rule based system for stock price prediction

    Pei-Chann Chang;Chen-Hao Liu

  • Kernel Sparse Representation-Based Classifier

    Li Zhang;Wei-Da Zhou;Pei-Chann Chang;Jing Liu

  • One-machine rescheduling heuristics with efficiency and stability as criteria

    S. David Wu;Robert H. Storer;Pei-Chann Chang

  • The development of a weighted evolving fuzzy neural network for PCB sales forecasting

    Pei-Chann Chang;Yen-Wen Wang;Chen-Hao Liu

  • A hybrid model combining case-based reasoning and fuzzy decision tree for medical data classification

    Chin-Yuan Fan;Pei-Chann Chang;Jyun-Jie Lin;J. C. Hsieh

  • Fuzzy Delphi and back-propagation model for sales forecasting in PCB industry

    Pei-Chann Chang;Yen-Wen Wang

  • Evolving and clustering fuzzy decision tree for financial time series data forecasting

    Robert K. Lai;Chin-Yuan Fan;Wei-Hsiu Huang;Pei-Chann Chang

  • A neural network with a case based dynamic window for stock trading prediction

    Pei-Chann Chang;Chen-Hao Liu;Jun-Lin Lin;Chin-Yuan Fan

  • Using a contextual entropy model to expand emotion words and their intensity for the sentiment classification of stock market news

    Liang-Chih Yu;Jheng-Long Wu;Pei-Chann Chang;Hsuan-Shou Chu

  • Monthly electricity demand forecasting based on a weighted evolving fuzzy neural network approach

    Pei-Chann Chang;Chin-Yuan Fan;Jyun-Jie Lin

  • Integrating a Piecewise Linear Representation Method and a Neural Network Model for Stock Trading Points Prediction

    Pei-Chann Chang;Chin-Yuan Fan;Chen-Hao Liu

  • Myocardial infarction classification with multi-lead ECG using hidden Markov models and Gaussian mixture models

    Pei-Chann Chang;Jyun-Jie Lin;Jui-Chien Hsieh;Julia Weng

  • Urban air quality forecasting based on multi-dimensional collaborative Support Vector Regression (SVR): A case study of Beijing-Tianjin-Shijiazhuang.

    Bing-Chun Liu;Arihant Binaykia;Pei-Chann Chang;Manoj Kumar Tiwari

  • Data clustering and fuzzy neural network for sales forecasting: A case study in printed circuit board industry

    Pei-Chann Chang;Chen-Hao Liu;Chin-Yuan Fan

  • Simultaneous dock assignment and sequencing of inbound trucks under a fixed outbound truck schedule in multi-door cross docking operations

    T.W. Liao;P.J. Egbelu;P.C. Chang

  • A novel model by evolving partially connected neural network for stock price trend forecasting

    Pei-Chann Chang;Di-Di Wang;Chang-Le Zhou

  • Combining SOM and fuzzy rule base for flow time prediction in semiconductor manufacturing factory

    P. C. Chang;T. W. Liao

  • Iterated time series prediction with multiple support vector regression models

    Li Zhang;Wei-Da Zhou;Pei-Chann Chang;Ji-Wen Yang

  • Two-phase sub population genetic algorithm for parallel machine-scheduling problem

    Pei-Chann Chang;Shih-Hsin Chen;Kun-Lin Lin

  • A Hybrid System Integrating a Wavelet and TSK Fuzzy Rules for Stock Price Forecasting

    Pei-Chann Chang;Chin-Yuan Fan

  • Sub-population genetic algorithm with mining gene structures for multiobjective flowshop scheduling problems

    Pei-Chann Chang;Shih-Hsin Chen;Chen-Hao Liu

Frequent Co-Authors

T. Warren Liao
T. Warren Liao Louisiana State University
Qingfu Zhang
Qingfu Zhang City University of Hong Kong
Manoj Kumar Tiwari
Manoj Kumar Tiwari Indian Institute of Technology Kharagpur
Rui Zhang
Rui Zhang National University of Singapore
Cheng Wu
Cheng Wu Tsinghua University
T.C.E. Cheng
T.C.E. Cheng Hong Kong Polytechnic University
Shiji Song
Shiji Song Tsinghua University
Mitsuo Gen
Mitsuo Gen Tokyo University of Science
Jing Liu
Jing Liu Xidian University
Raymond Chiong
Raymond Chiong University of Newcastle Australia

External Links

Personal website of Pei-Chann Chang

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Finally, be strategic by targeting most in demand masters degrees. Computer science intersects with highly sought-after fields like artificial intelligence, business analytics, and cybersecurity, providing numerous pathways to a rewarding career.

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