World's Best Scientists 2026 revealed!
Dalibor Petković

Dalibor Petković

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Rising Stars
2025

D-Index & Metrics

Rising Stars

D-Index
51
Citations
9159
World Ranking
296
National Ranking
1

Mechanical and Aerospace Engineering

D-Index
52
Citations
8687
World Ranking
1075
National Ranking
1

Dalibor Petković publication distribution in Mechanical and Aerospace Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mechanical and Aerospace Engineering in 2026. The highlighted bar marks where Dalibor Petković sits on this spectrum.

47–56 publications: 10 scientists 57–66 publications: 23 scientists 67–76 publications: 32 scientists 77–86 publications: 62 scientists 87–96 publications: 67 scientists 97–106 publications: 91 scientists 107–116 publications: 113 scientists 117–126 publications: 115 scientists 127–136 publications: 130 scientists 137–146 publications: 140 scientists 147–156 publications: 155 scientists 157–166 publications: 132 scientists 167–176 publications: 133 scientists 177–186 publications: 130 scientists 187–196 publications: 140 scientists 197–206 publications: 115 scientists 207–216 publications: 125 scientists 217–226 publications: 117 scientists 227–236 publications: 99 scientists 237–246 publications: 92 scientists 247–256 publications: 100 scientists 257–266 publications: 95 scientists 267–276 publications: 88 scientists 277–286 publications: 77 scientists 287–296 publications: 74 scientists 297–306 publications: 74 scientists 307–316 publications: 62 scientists 317–326 publications: 70 scientists 327–336 publications: 59 scientists 337–346 publications: 58 scientists 347–356 publications: 45 scientists 357–366 publications: 44 scientists 367–376 publications: 36 scientists 377–386 publications: 41 scientists 387–396 publications: 32 scientists 397–406 publications: 23 scientists 407–416 publications: 28 scientists 417–426 publications: 27 scientists 427–436 publications: 25 scientists 437–446 publications: 23 scientists 447–456 publications: 23 scientists 457–466 publications: 20 scientists 467–476 publications: 12 scientists 477–486 publications: 24 scientists 487–496 publications: 18 scientists 497–506 publications: 12 scientists 507–516 publications: 13 scientists 517–526 publications: 21 scientists 527–536 publications: 12 scientists 537–546 publications: 8 scientists 547–556 publications: 16 scientists 557–566 publications: 3 scientists 567–576 publications: 11 scientists 577–586 publications: 6 scientists 587–596 publications: 5 scientists 597–606 publications: 6 scientists 607–616 publications: 7 scientists 617–626 publications: 7 scientists 627–636 publications: 10 scientists 637–646 publications: 4 scientists 647–656 publications: 3 scientists 657–658 publications: 2 scientists 659+ publications: 100 scientists
47 publications 659+

This scientist: 214 publications — 49th percentile

49% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 659 publications or more.

Dalibor Petković D-index placement in Mechanical and Aerospace Engineering in 2026

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

30 D-Index: 83 scientists 31 D-Index: 113 scientists 32 D-Index: 144 scientists 33 D-Index: 153 scientists 34 D-Index: 189 scientists 35 D-Index: 158 scientists 36 D-Index: 139 scientists 37 D-Index: 127 scientists 38 D-Index: 130 scientists 39 D-Index: 126 scientists 40 D-Index: 104 scientists 41 D-Index: 100 scientists 42 D-Index: 107 scientists 43 D-Index: 101 scientists 44 D-Index: 103 scientists 45 D-Index: 79 scientists 46 D-Index: 88 scientists 47 D-Index: 70 scientists 48 D-Index: 83 scientists 49 D-Index: 44 scientists 50 D-Index: 64 scientists 51 D-Index: 56 scientists 52 D-Index: 50 scientists 53 D-Index: 48 scientists 54 D-Index: 58 scientists 55 D-Index: 52 scientists 56 D-Index: 48 scientists 57 D-Index: 42 scientists 58 D-Index: 34 scientists 59 D-Index: 42 scientists 60 D-Index: 37 scientists 61 D-Index: 42 scientists 62 D-Index: 44 scientists 63 D-Index: 22 scientists 64 D-Index: 33 scientists 65 D-Index: 29 scientists 66 D-Index: 23 scientists 67 D-Index: 29 scientists 68 D-Index: 24 scientists 69 D-Index: 19 scientists 70 D-Index: 34 scientists 71 D-Index: 26 scientists 72 D-Index: 19 scientists 73 D-Index: 18 scientists 74 D-Index: 19 scientists 75 D-Index: 14 scientists 76 D-Index: 19 scientists 77 D-Index: 8 scientists 78 D-Index: 18 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 17 scientists 82 D-Index: 11 scientists 83 D-Index: 16 scientists 84 D-Index: 7 scientists 85 D-Index: 9 scientists 86 D-Index: 8 scientists 87 D-Index: 6 scientists 88 D-Index: 6 scientists 89 D-Index: 7 scientists 90 D-Index: 10 scientists 91 D-Index: 4 scientists 92 D-Index: 4 scientists 93+ D-Index: 100 scientists
30 D-Index 93+

This scientist: 52 D-Index — 70th percentile

70% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 93 D-Index or more.

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Dalibor Petković is affiliated with the University of Nis in Serbia and has contributed extensively to the field of engineering, with a particular focus on electrical and electronic engineering, biomedical engineering, artificial intelligence, mechanical engineering, and control and systems engineering.

Their recent publications cover a range of topics in both theoretical and applied research. Notable papers include:

  • E-learning perspectives in higher education institutions, 2021, Technological Forecasting and Social Change
  • Application of distance learning in mathematics through adaptive neuro-fuzzy learning method, 2021, Computers & Electrical Engineering
  • Estimation of optimal fertilizers for optimal crop yield by adaptive neuro fuzzy logic, 2021, Rhizosphere
  • Selection of the most influential parameters on vectorial crystal growth of highly oriented vertically aligned carbon nanotubes by adaptive neuro-fuzzy technique, 2020, International Journal of Hydromechatronics
  • Neuro-fuzzy estimation of reference crop evapotranspiration by neuro fuzzy logic based on weather conditions, 2020, Computers and Electronics in Agriculture

Their research topics demonstrate a strong focus on advanced machining and optimization techniques, biodiesel production and applications, thermochemical biomass conversion processes, online learning and analytics, greenhouse technology and climate control, surface treatment and coatings, and process optimization and integration.

Dalibor Petković has frequently published in several academic venues, including:

  • Biomass Conversion and Biorefinery
  • International Journal of Hydromechatronics
  • Natural Hazards
  • Multimedia Tools and Applications
  • Computer Applications in Engineering Education

The scientist collaborates regularly with a number of coauthors, among the most frequent being:

  • Nebojša Denić
  • Biljana Petković
  • Boris Kuzman
  • Jelena Stojanović
  • Miloš Milovančević

Dalibor Petković's research contributions span across interdisciplinary applications, including artificial intelligence methods such as adaptive neuro-fuzzy techniques, and cover practical implementations from education technology to agricultural optimization and materials science.

Best Publications

  • A support vector machine–firefly algorithm-based model for global solar radiation prediction

    Lanre Olatomiwa;Lanre Olatomiwa;Saad Mekhilef;Shahaboddin Shamshirband;Kasra Mohammadi

  • A new hybrid support vector machine–wavelet transform approach for estimation of horizontal global solar radiation

    Kasra Mohammadi;Shahaboddin Shamshirband;Chong Wen Tong;Muhammad Arif

  • Potential of adaptive neuro fuzzy inference system for evaluating the factors affecting steel-concrete composite beam's shear strength

    M. Safa;M. Shariati;Z. Ibrahim;A. Toghroli

  • Adaptive neuro-fuzzy approach for wind turbine power coefficient estimation

    Dalibor Petković;Žarko Ćojbašič;Vlastimir Nikolić

  • Support vector regression based prediction of global solar radiation on a horizontal surface

    Kasra Mohammadi;Shahaboddin Shamshirband;Mohammad Hossein Anisi;Khubaib Amjad Alam

  • Adaptive neuro-fuzzy maximal power extraction of wind turbine with continuously variable transmission

    Dalibor Petković;Žarko Ćojbašić;Vlastimir Nikolić;Shahaboddin Shamshirband

  • Adaptive neuro-fuzzy approach for solar radiation prediction in Nigeria

    Lanre Olatomiwa;Lanre Olatomiwa;Saad Mekhilef;Shahaboddin Shamshirband;Dalibor Petković

  • RETRACTED ARTICLE: Analysis of influential factors forpredicting the shear strength of a V-shaped angle shear connector in composite beamsusing an adaptive neuro-fuzzy technique

    I. Mansouri;M. Shariati;M. Safa;Z. Ibrahim

  • Adaptive neuro fuzzy controller for adaptive compliant robotic gripper

    Dalibor Petković;Mirna Issa;Nenad D. Pavlović;Lena Zentner

  • A comparative evaluation for identifying the suitability of extreme learning machine to predict horizontal global solar radiation

    Shahaboddin Shamshirband;Kasra Mohammadi;Por Lip Yee;Dalibor Petković

  • Performance investigation of micro- and nano-sized particle erosion in a 90° elbow using an ANFIS model

    Shahaboddin Shamshirband;Amir Malvandi;Arash Karimipour;Marjan Goodarzi

  • Potential of adaptive neuro-fuzzy system for prediction of daily global solar radiation by day of the year

    Kasra Mohammadi;Shahaboddin Shamshirband;Chong Wen Tong;Khubaib Amjad Alam

  • Adaptive neuro-fuzzy estimation of conductive silicone rubber mechanical properties

    Dalibor Petković;Mirna Issa;Nenad D. Pavlović;Nenad T. Pavlović

  • Support vector regression methodology for wind turbine reaction torque prediction with power-split hydrostatic continuous variable transmission

    Shahaboddin Shamshirband;Dalibor Petković;Amineh Amini;Nor Badrul Anuar

  • Estimating the diffuse solar radiation using a coupled support vector machine–wavelet transform model

    Shahaboddin Shamshirband;Kasra Mohammadi;Hossein Khorasanizadeh;Por Lip Yee

  • Adaptive neuro-fuzzy estimation of autonomic nervous system parameters effect on heart rate variability

    D. Petković;Ž. Ćojbašić

  • Prediction of heat load in district heating systems by Support Vector Machine with Firefly searching algorithm

    Eiman Tamah Al-Shammari;Afram Keivani;Shahaboddin Shamshirband;Ali Mostafaeipour

  • Wind farm efficiency by adaptive neuro-fuzzy strategy

    Dalibor Petković;Nenad T. Pavlović;Žarko Ćojbašić

  • Forecasting of consumers heat load in district heating systems using the support vector machine with a discrete wavelet transform algorithm

    Milan Protić;Shahaboddin Shamshirband;Dalibor Petković;Almas Abbasi

  • Sensor Data Fusion by Support Vector Regression Methodology—A Comparative Study

    Shahaboddin Shamshirband;Dalibor Petkovic;Hossein Javidnia;Abdullah Gani

  • Wind speed parameters sensitivity analysis based on fractals and neuro-fuzzy selection technique

    Vlastimir Nikolić;Vojislav V. Mitić;Ljubiša Kocić;Dalibor Petković

Frequent Co-Authors

Shahab S. Band
Shahab S. Band National Yunlin University of Science and Technology
Nor Badrul Anuar
Nor Badrul Anuar University of Malaya
Kasra Mohammadi
Kasra Mohammadi University of Utah
Miss Laiha Mat Kiah
Miss Laiha Mat Kiah University of Malaya
Abdullah Gani
Abdullah Gani University of Malaya
Ali Mostafaeipour
Ali Mostafaeipour California State University, Fullerton
Hossein Bonakdari
Hossein Bonakdari University of Ottawa
Ahmad Sedaghat
Ahmad Sedaghat Australian University Kuwait
Saad Mekhilef
Saad Mekhilef Swinburne University of Technology
Ainuddin Wahid Abdul Wahab
Ainuddin Wahid Abdul Wahab Information Technology University

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