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Sancho Salcedo-Sanz

Sancho Salcedo-Sanz

University of Alcalá
Spain

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Computer Science
Spain
2025

D-Index & Metrics

Computer Science

D-Index
62
Citations
13479
World Ranking
2943
National Ranking
36

Sancho Salcedo-Sanz 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 Sancho Salcedo-Sanz 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: 411 publications — 88th percentile

88% of scientists in this discipline score the same or lower.

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

Sancho Salcedo-Sanz 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 Sancho Salcedo-Sanz 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: 62 D-Index — 80th percentile

80% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Computer Science in Spain Leader Award
  • 2022 - Research.com Computer Science in Spain Leader Award

Overview

Sancho Salcedo-Sanz is affiliated with the University of Alcalá in Spain. Their research primarily spans the fields of Engineering and Computer Science, with a notable focus on Electrical and Electronic Engineering, Artificial Intelligence, Environmental Engineering, Atmospheric Science, and Civil and Structural Engineering.

Their scholarly contributions emphasize key topics such as Energy Load and Power Forecasting, Solar Radiation and Photovoltaics, Meteorological Phenomena and Simulations, Electric Power System Optimization, Hydrological Forecasting Using AI, Wind and Air Flow Studies, and Climate Variability and Models.

Recent papers authored by or connected to Salcedo-Sanz cover diverse subjects and have appeared in various scientific venues. Notable examples include:

  • "Heat Waves: Physical Understanding and Scientific Challenges" (2023), Reviews of Geophysics
  • "Near real-time wind speed forecast model with bidirectional LSTM networks" (2023), Renewable Energy
  • "Deep learning CNN-LSTM-MLP hybrid fusion model for feature optimizations and daily solar radiation prediction" (2022), Measurement
  • "Stacked LSTM Sequence-to-Sequence Autoencoder with Feature Selection for Daily Solar Radiation Prediction: A Review and New Modeling Results" (2022), Energies
  • "Multi-task learning for the prediction of wind power ramp events with deep neural networks" (2020), Neural Networks

Frequent coauthors collaborating with Salcedo-Sanz include:

  • Jorge Pérez-Aracil
  • David Casillas-Pérez
  • Ravinesh C. Deo
  • S. Jiménez-Fernández
  • César Peláez-Rodríguez

Their work is published predominantly in the following venues:

  • IEEE Access
  • SSRN Electronic Journal
  • arXiv (Cornell University)
  • Renewable Energy
  • Applied Energy

Best Publications

  • Bio-inspired computation: Where we stand and what's next

    Javier Del Ser;Javier Del Ser;Eneko Osaba;Daniel Molina;Xin-She Yang

  • Survey A survey on applications of the harmony search algorithm

    D. Manjarres;I. Landa-Torres;S. Gil-Lopez;J. Del Ser

  • Predicting compressive strength of lightweight foamed concrete using extreme learning machine model

    Zaher Mundher Yaseen;Ravinesh C. Deo;Ameer Hilal;Abbas M. Abd

  • A Critical Review of Robustness in Power Grids Using Complex Networks Concepts

    Lucas Cuadra;Sancho Salcedo-Sanz;Javier Del Ser;Silvia Jiménez-Fernández

  • Support vector machines in engineering: an overview

    S. Salcedo-Sanz;J. L. Rojo-Álvarez;M. Martínez-Ramón;G. Camps-Valls

  • Short term wind speed prediction based on evolutionary support vector regression algorithms

    Sancho Salcedo-Sanz;Emilio G. Ortiz-Garcıa;Ángel M. Pérez-Bellido;Antonio Portilla-Figueras

  • Hybridizing the fifth generation mesoscale model with artificial neural networks for short-term wind speed prediction

    Sancho Salcedo-Sanz;Ángel M. Pérez-Bellido;Emilio G. Ortiz-García;Antonio Portilla-Figueras

  • Machine learning information fusion in Earth observation: A comprehensive review of methods, applications and data sources

    Sancho Salcedo-Sanz;Pedram Ghamisi;Maria Piles;Martin Werner

  • The Coral Reefs Optimization Algorithm: A Novel Metaheuristic for Efficiently Solving Optimization Problems

    S. Salcedo-Sanz;J. Del Ser;I. Landa-Torres;S. Gil-López

  • Daily global solar radiation prediction based on a hybrid Coral Reefs Optimization – Extreme Learning Machine approach

    S. Salcedo-Sanz;C. Casanova-Mateo;A. Pastor-Sánchez;M. Sánchez-Girón

  • Feature selection in machine learning prediction systems for renewable energy applications

    S. Salcedo-Sanz;L. Cornejo-Bueno;L. Prieto;D. Paredes

  • Modern meta-heuristics based on nonlinear physics processes: A review of models and design procedures

    S. Salcedo-Sanz

  • Feature selection in wind speed prediction systems based on a hybrid coral reefs optimization – Extreme learning machine approach

    S. Salcedo-Sanz;A. Pastor-Sánchez;L. Prieto;A. Blanco-Aguilera

  • A new grouping genetic algorithm for clustering problems

    L.E. Agustin-Blas;S. Salcedo-Sanz;S. Jiménez-Fernández;L. Carro-Calvo

  • Seeding evolutionary algorithms with heuristics for optimal wind turbines positioning in wind farms

    B. Saavedra-Moreno;S. Salcedo-Sanz;A. Paniagua-Tineo;L. Prieto

  • Survey: A survey of repair methods used as constraint handling techniques in evolutionary algorithms

    Sancho Salcedo-Sanz

  • A Review of Classification Problems and Algorithms in Renewable Energy Applications

    María Pérez-Ortiz;Silvia Jiménez-Fernández;Pedro A. Gutiérrez;Enrique Alexandre

  • Letters: Accurate short-term wind speed prediction by exploiting diversity in input data using banks of artificial neural networks

    Sancho Salcedo-Sanz;Ángel M. Pérez-Bellido;Emilio G. Ortiz-García;Antonio Portilla-Figueras

  • A mixed neural-genetic algorithm for the broadcast scheduling problem

    S. Salcedo-Sanz;C. Bousono-Calzon;A.R. Figueiras-Vidal

  • A novel Grouping Genetic Algorithm–Extreme Learning Machine approach for global solar radiation prediction from numerical weather models inputs

    A. Aybar-Ruiz;S. Jiménez-Fernández;L. Cornejo-Bueno;C. Casanova-Mateo

  • A hybrid Hopfield network-genetic algorithm approach for the terminal assignment problem

    S. Salcedo-Sanz;Xin Yao

Frequent Co-Authors

Javier Del Ser
Javier Del Ser University of the Basque Country
Pedro Antonio Gutiérrez
Pedro Antonio Gutiérrez University of Córdoba
César Hervás-Martínez
César Hervás-Martínez University of Córdoba
Ricardo García-Herrera
Ricardo García-Herrera Complutense University of Madrid
Xin Yao
Xin Yao Lingnan University
Fernando Perez-Cruz
Fernando Perez-Cruz ETH Zurich
Ravinesh C. Deo
Ravinesh C. Deo University of Southern Queensland
Zong Woo Geem
Zong Woo Geem Gachon University
Gustau Camps-Valls
Gustau Camps-Valls University of Valencia
David Camacho
David Camacho Technical University of Madrid

External Links

Personal website of Sancho Salcedo-Sanz Google Scholar page

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Best Scientists Citing Sancho Salcedo-Sanz

Javier Del Ser

Javier Del Ser

University of the Basque Country

Publications: 72

Ravinesh C. Deo

Ravinesh C. Deo

University of Southern Queensland

Publications: 47

Zaher Mundher Yaseen

Zaher Mundher Yaseen

King Fahd University of Petroleum and Minerals

Publications: 30

Leandro dos Santos Coelho

Leandro dos Santos Coelho

Federal University of Paraná

Publications: 28

Shahab S. Band

Shahab S. Band

National Yunlin University of Science and Technology

Publications: 27

César Hervás-Martínez

César Hervás-Martínez

University of Córdoba

Publications: 22

David Camacho

David Camacho

Technical University of Madrid

Publications: 22

Jianzhou Wang

Jianzhou Wang

Macau University of Science and Technology

Publications: 21

Ozgur Kisi

Ozgur Kisi

Ilia State University

Publications: 20

Hui Liu

Hui Liu

Central South University

Publications: 19

Dalibor Petković

Dalibor Petković

University of Nis

Publications: 19

Viviana Cocco Mariani

Viviana Cocco Mariani

Pontifícia Universidade Católica do Paraná

Publications: 18

Pedro Antonio Gutiérrez

Pedro Antonio Gutiérrez

University of Córdoba

Publications: 18

Zong Woo Geem

Zong Woo Geem

Gachon University

Publications: 14

Richard J. A. M. Stevens

Richard J. A. M. Stevens

University of Twente

Publications: 13

Mohammed Azmi Al-Betar

Mohammed Azmi Al-Betar

Ajman University of Science and Technology

Publications: 13

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