World's Best Scientists 2026 revealed!
Francisco Martínez-Álvarez

Francisco Martínez-Álvarez

D-Index & Metrics

Computer Science

D-Index
41
Citations
6668
World Ranking
8883
National Ranking
131

Francisco Martínez-Álvarez 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 Francisco Martínez-Álvarez 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: 161 publications — 31st percentile

31% of scientists in this discipline score the same or lower.

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

Francisco Martínez-Álvarez 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 Francisco Martínez-Álvarez 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: 41 D-Index — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Overview

Francisco Martínez-Álvarez is affiliated with Pablo de Olavide University in Spain. Their research focuses primarily on computer science, engineering, and environmental science, with significant contributions in artificial intelligence, management science and operations research, electrical and electronic engineering, signal processing, and plant science.

Their work covers key topics such as energy load and power forecasting, time series analysis and forecasting, stock market forecasting methods, data stream mining techniques, forecasting techniques and applications, smart agriculture and AI, and machine learning and data classification.

Recent publications include:

  • Deep Learning for Time Series Forecasting: A Survey, 2020, Big Data
  • A deep LSTM network for the Spanish electricity consumption forecasting, 2022, Neural Computing and Applications
  • Electricity consumption forecasting based on ensemble deep learning with application to the Algerian market, 2021, Energy
  • Deformation forecasting of a hydropower dam by hybridizing a long short-term memory deep learning network with the coronavirus optimization algorithm, 2022, Computer-Aided Civil and Infrastructure Engineering
  • Big data time series forecasting based on pattern sequence similarity and its application to the electricity demand, 2020, Information Sciences

Frequent co-authors in Martínez-Álvarez's research include Alicia Troncoso, M. Martínez-Ballesteros, G. Asencio-Cortés, M. J. Jiménez-Navarro, and J. F. Torres.

Several academic journals have published multiple papers by Martínez-Álvarez, including Neurocomputing, SSRN Electronic Journal, Information Sciences, Applied Sciences, and Computers & Geosciences.

Martínez-Álvarez has also contributed to books published mainly by Springer International Publishing, Springer Science+Business Media, and Springer Nature. Titles include the 18th and 17th International Conferences on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023, SOCO 2022), Hybrid Artificial Intelligent Systems (2022, 2023), and Computational Intelligence for Water and Environmental Sciences (2022).

Best Publications

  • Deep Learning for Time Series Forecasting: A Survey.

    José F. Torres;Dalil Hadjout;Abderrazak Sebaa;Francisco Martínez-Álvarez

  • A novel deep learning neural network approach for predicting flash flood susceptibility: A case study at a high frequency tropical storm area.

    Dieu Tien Bui;Nhat-Duc Hoang;Francisco Martínez-Álvarez;Phuong-Thao Thi Ngo

  • Energy Time Series Forecasting Based on Pattern Sequence Similarity

    Francisco Martinez Alvarez;A Troncoso;J C Riquelme;Jesus S Aguilar Ruiz

  • Earthquake magnitude prediction in Hindukush region using machine learning techniques

    Khawaja M. Asim;Francisco Martínez-Álvarez;A. Basit;Talat Iqbal

  • Multi-step forecasting for big data time series based on ensemble learning

    A. Galicia;R. Talavera-Llames;A. Troncoso;I. Koprinska

  • Neural networks to predict earthquakes in Chile

    J. Reyes;A. Morales-Esteban;F. MartíNez-ÁLvarez

  • A deep LSTM network for the Spanish electricity consumption forecasting

    Unknown

  • A Survey on Data Mining Techniques Applied to Electricity-Related Time Series Forecasting

    Francisco Martínez-Álvarez;Alicia Troncoso;Gualberto Asencio-Cortés;José C. Riquelme

  • A novel ensemble modeling approach for the spatial prediction of tropical forest fire susceptibility using LogitBoost machine learning classifier and multi-source geospatial data

    Mahyat Shafapour Tehrany;Simon Jones;Farzin Shabani;Farzin Shabani;Francisco Martínez-Álvarez

  • Coronavirus Optimization Algorithm: A Bioinspired Metaheuristic Based on the COVID-19 Propagation Model.

    Francisco Martínez-Álvarez;Gualberto Asencio-Cortés;José F. Torres;David Gutiérrez-Avilés

  • Earthquake prediction model using support vector regressor and hybrid neural networks.

    Khawaja M Asim;Adnan Idris;Talat Iqbal;Francisco Martínez-Álvarez

  • A scalable approach based on deep learning for big data time series forecasting

    J.F. Torres;A. Galicia;A. Troncoso;F. Martínez-Álvarez

  • Determining the best set of seismicity indicators to predict earthquakes. Two case studies: Chile and the Iberian Peninsula

    F. Martínez-Álvarez;J. Reyes;A. Morales-Esteban;C. Rubio-Escudero

  • Pattern recognition to forecast seismic time series

    A. Morales-Esteban;F. Martínez-Álvarez;A. Troncoso;J. L. Justo

  • Big Data Analytics for Discovering Electricity Consumption Patterns in Smart Cities

    Rubén Pérez-Chacón;José M. Luna-Romera;Alicia Troncoso;Francisco Martínez-Álvarez

  • A comparison of machine learning regression techniques for LiDAR-derived estimation of forest variables

    J. García-Gutiérrez;F. Martínez-Álvarez;A. Troncoso;J.C. Riquelme

  • Medium---large earthquake magnitude prediction in Tokyo with artificial neural networks

    G. Asencio-Cortés;F. Martínez-Álvarez;A. Troncoso;A. Morales-Esteban

  • Cluster Analysis and Applications

    Unknown

  • A fast partitioning algorithm using adaptive Mahalanobis clustering with application to seismic zoning

    Antonio Morales-Esteban;Francisco Martínez-Álvarez;Sanja Scitovski;Rudolf Scitovski

  • Earthquake prediction in seismogenic areas of the Iberian Peninsula based on computational intelligence

    A. Morales-Esteban;F. Martínez-Álvarez;J. Reyes

  • Mining quantitative association rules based on evolutionary computation and its application to atmospheric pollution

    M. Martínez-Ballesteros;A. Troncoso;F. Martínez-Álvarez;J. C. Riquelme

  • A sensitivity study of seismicity indicators in supervised learning to improve earthquake prediction

    G. Asencio-Cortés;F. Martínez-Álvarez;A. Morales-Esteban;J. Reyes

  • Seismic indicators based earthquake predictor system using Genetic Programming and AdaBoost classification

    Khawaja M. Asim;Adnan Idris;Talat Iqbal;Francisco Martínez-Álvarez

Frequent Co-Authors

Alicia Troncoso
Alicia Troncoso Pablo de Olavide University
José C. Riquelme
José C. Riquelme University of Seville
Dieu Tien Bui
Dieu Tien Bui University of South-Eastern Norway
José Miguel Azañón
José Miguel Azañón University of Granada
Nhat-Duc Hoang
Nhat-Duc Hoang Duy Tan University
Emilio Corchado
Emilio Corchado University of Salamanca
Pijush Samui
Pijush Samui National Institute of Technology Patna
Simon Jones
Simon Jones Microsoft (United States)
Abdul Basit
Abdul Basit University College London

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