World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
53
Citations
9216
World Ranking
3465
National Ranking
706

Dazhi Yang publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Dazhi Yang sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 139 publications — 22nd percentile

22% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Dazhi Yang D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Dazhi Yang sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 53 D-Index — 66th percentile

66% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Dazhi Yang is affiliated with the Harbin Institute of Technology in China. Their research spans multiple areas primarily within engineering and computer science, with significant contributions to electrical and electronic engineering, artificial intelligence, renewable energy, sustainability, environmental studies, global and planetary change, and atmospheric science.

Their publication record includes high-impact research in several frequent venues, notably:

  • Solar Energy
  • Renewable and Sustainable Energy Reviews
  • Journal of Renewable and Sustainable Energy
  • Energy
  • Advances in Atmospheric Sciences

Dazhi Yang has authored and coauthored numerous papers covering key topics such as solar radiation and photovoltaics, energy load and power forecasting, photovoltaic system optimization techniques, solar thermal and photovoltaic systems, meteorological phenomena and simulations, atmospheric aerosols and clouds, and advanced battery technologies research.

Frequent collaborators of Dazhi Yang include Xiangao Xia, Bai Liu, Martin János Mayer, Chao Lyu, and Guoming Yang.

Representative recent publications by Dazhi Yang are:

  • "A review of solar forecasting, its dependence on atmospheric sciences and implications for grid integration: Towards carbon neutrality," 2022, Renewable and Sustainable Energy Reviews
  • "Verification of deterministic solar forecasts," 2020, Solar Energy
  • "Worldwide validation of 8 satellite-derived and reanalysis solar radiation products: A preliminary evaluation and overall metrics for hourly data over 27 years," 2020, Solar Energy
  • "Choice of clear-sky model in solar forecasting," 2020, Journal of Renewable and Sustainable Energy

Among the topics covered in these works are solar forecasting methodologies, evaluation of satellite-derived solar radiation data, and model selection for clear-sky irradiance prediction. Earlier work relevant to energy forecasting includes collaboration with Tao Hong on a review of energy forecasting published in 2020 in the IEEE Open Access Journal of Power and Energy.

Best Publications

  • Energy forecasting: A review and outlook

    Tao Hong;Pierre Pinson;Yi Wang;Rafał Weron

  • History and trends in solar irradiance and PV power forecasting: A preliminary assessment and review using text mining

    Dazhi Yang;Jan Kleissl;Christian A. Gueymard;Hugo T.C. Pedro

  • A review of solar forecasting, its dependence on atmospheric sciences and implications for grid integration: Towards carbon neutrality

    Unknown

  • Hourly solar irradiance time series forecasting using cloud cover index

    Dazhi Yang;Panida Jirutitijaroen;Wilfred M. Walsh

  • Worldwide validation of CAMS and MERRA-2 reanalysis aerosol optical depth products using 15 years of AERONET observations

    Christian A. Gueymard;Dazhi Yang

  • Automatic hourly solar forecasting using machine learning models

    Gokhan Mert Yagli;Dazhi Yang;Dipti Srinivasan

  • Solar radiation on inclined surfaces: Corrections and benchmarks

    Dazhi Yang

  • Short-term solar irradiance forecasting using exponential smoothing state space model

    Zibo Dong;Dazhi Yang;Thomas Reindl;Wilfred M. Walsh

  • Verification of deterministic solar forecasts

    Dazhi Yang;Stefano Alessandrini;Javier Antonanzas;Fernando Antonanzas-Torres

  • Short term solar irradiance forecasting using a mixed wavelet neural network

    Vishal Sharma;Dazhi Yang;Wilfred Walsh;Thomas Reindl

  • Worldwide validation of 8 satellite-derived and reanalysis solar radiation products: A preliminary evaluation and overall metrics for hourly data over 27 years

    Dazhi Yang;Jamie M. Bright

  • Forecasting of global horizontal irradiance by exponential smoothing, using decompositions

    Dazhi Yang;Vishal Sharma;Zhen Ye;Li Hong Idris Lim

  • Solar irradiance forecasting using spatial-temporal covariance structures and time-forward kriging

    Dazhi Yang;Chaojun Gu;Zibo Dong;Panida Jirutitijaroen

  • Very short term irradiance forecasting using the lasso

    Dazhi Yang;Zhen Ye;Li Hong Idris Lim;Zibo Dong

  • Optimal Orientation and Tilt Angle for Maximizing in-Plane Solar Irradiation for PV Applications in Singapore

    Yong Sheng Khoo;Andre Nobre;Raghav Malhotra;Dazhi Yang

  • A guideline to solar forecasting research practice: Reproducible, operational, probabilistic or physically-based, ensemble, and skill (ROPES)

    Dazhi Yang

  • A novel hybrid approach based on self-organizing maps, support vector regression and particle swarm optimization to forecast solar irradiance

    Zibo Dong;Dazhi Yang;Thomas Reindl;Wilfred M. Walsh

  • A Siting and Sizing Optimization Approach for PV–Battery–Diesel Hybrid Systems

    Carlos D. Rodriguez-Gallegos;Oktoviano Gandhi;Dazhi Yang;Manuel S. Alvarez-Alvarado

  • A Linear Identification of Diode Models from Single $I$ – $V$ Characteristics of PV Panels

    Li Hong Idris Lim;Zhen Ye;Jiaying Ye;Dazhi Yang

  • Satellite image analysis and a hybrid ESSS/ANN model to forecast solar irradiance in the tropics

    Zibo Dong;Dazhi Yang;Thomas Reindl;Wilfred M. Walsh

  • Very short-term irradiance forecasting at unobserved locations using spatio-temporal kriging

    Aloysius W. Aryaputera;Dazhi Yang;Lu Zhao;Wilfred M. Walsh

Frequent Co-Authors

Thomas Reindl
Thomas Reindl National University of Singapore
Dipti Srinivasan
Dipti Srinivasan National University of Singapore
Christian A. Gueymard
Christian A. Gueymard University of Central Florida
Ricardo Rüther
Ricardo Rüther Universidade Federal de Santa Catarina
Jan Kleissl
Jan Kleissl University of California, San Diego
Jie Zhang
Jie Zhang The University of Texas at Dallas
Sanjib Kumar Panda
Sanjib Kumar Panda National University of Singapore
Hamidreza Zareipour
Hamidreza Zareipour University of Calgary
Bri-Mathias Hodge
Bri-Mathias Hodge University of Colorado Boulder
Armin G. Aberle
Armin G. Aberle National University of Singapore

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