Suchergebnisse - Application of Genetic Programming in Machine Learning

  1. 1
  2. 2

    PID Tuning Using Differential Evolution With Success-Based Particle Adaptations von Victor Parque, Alaa Khalifa

    ISSN: 2169-3536
    Veröffentlicht: Institute of Electrical and Electronics Engineers (IEEE) 01.01.2023
    Veröffentlicht in IEEE Access (01.01.2023)
    Volltext
    Journal Article
  3. 3

    BinHOA: Efficient Binary Horse Herd Optimization Method for Feature Selection: Analysis and Validations von Dina A. Elmanakhly, Mohamed Saleh, Essam A. Rashed, Mohamed Abdel‐Basset

    ISSN: 2169-3536
    Veröffentlicht: Institute of Electrical and Electronics Engineers (IEEE) 01.01.2022
    Veröffentlicht in IEEE Access (01.01.2022)
    Volltext
    Journal Article
  4. 4

    Multi-variant differential evolution algorithm for feature selection von Somaia Awad Hassan, Ashraf Mohamed Hemeida, Salem Alkhalaf, Al-Attar Ali Mohamed, Tomonobu Senjyu

    ISSN: 2045-2322
    Veröffentlicht: Springer Science and Business Media LLC 14.10.2020
    Veröffentlicht in Scientific Reports (14.10.2020)
    Volltext
    Journal Article
  5. 5

    PARAMETER ADAPTATION FOR ANT COLONY SYSTEM IN WIRELESS SENSOR NETWORK von Husna Jamal Abdul Nasir, Ku Ruhana Ku‐Mahamud, Eiji Kamioka

    ISSN: 1675-414X, 2180-3862
    Veröffentlicht: UUM Press, Universiti Utara Malaysia 01.01.2019
    Veröffentlicht in Journal of Information and Communication Technology (01.01.2019)
    Volltext
    Journal Article
  6. 6

    Machine learning-based downscaling: application of multi-gene genetic programming for downscaling daily temperature at Dogonbadan, Iran, under CMIP6 scenarios von Niazkar, Majid, Goodarzi, Mohammad Reza, Fatehifar, Atiyeh, Abedi, Mohammad Javad

    ISSN: 0177-798X, 1434-4483
    Veröffentlicht: Vienna Springer Vienna 01.01.2023
    Veröffentlicht in Theoretical and applied climatology (01.01.2023)
    “… In this study, two machine learning (ML) models, named multi-gene genetic programming (MGGP …”
    Volltext
    Journal Article
  7. 7
  8. 8

    Hydrologically Informed Machine Learning for Rainfall‐Runoff Modeling: A Genetic Programming‐Based Toolkit for Automatic Model Induction von Chadalawada, Jayashree, Herath, H. M. V. V., Babovic, Vladan

    ISSN: 0043-1397, 1944-7973
    Veröffentlicht: Washington John Wiley & Sons, Inc 01.04.2020
    Veröffentlicht in Water resources research (01.04.2020)
    “… Models of water resources systems are conceived to capture the underlying environmental dynamics occurring within watersheds. All such models can be regarded …”
    Volltext
    Journal Article
  9. 9

    Balanced Cartesian Genetic Programming via migration and opposition-based learning: application to symbolic regression von Yazdani, Samaneh, Shanbehzadeh, Jamshid

    ISSN: 1389-2576, 1573-7632
    Veröffentlicht: Boston Springer US 01.06.2015
    Veröffentlicht in Genetic programming and evolvable machines (01.06.2015)
    “… Cartesian Genetic Programming (CGP) is a generalization of the graph based genetic programming …”
    Volltext
    Journal Article
  10. 10

    Comparison of approaches for machine-learning optimization of neural networks for detecting gene-gene interactions in genetic epidemiology von Motsinger-Reif, Alison A., Dudek, Scott M., Hahn, Lance W., Ritchie, Marylyn D.

    ISSN: 0741-0395, 1098-2272
    Veröffentlicht: Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.05.2008
    Veröffentlicht in Genetic epidemiology (01.05.2008)
    “… To solve this, machinelearning approaches have been suggested to evolve the best NN architecture for a particular data set …”
    Volltext
    Journal Article
  11. 11

    Predicting discharge coefficient of triangular labyrinth weir using extreme learning machine, artificial neural network and genetic programming von Karami, Hojat, Karimi, Sohrab, Bonakdari, Hossein, Shamshirband, Shahabodin

    ISSN: 0941-0643, 1433-3058
    Veröffentlicht: London Springer London 01.06.2018
    Veröffentlicht in Neural computing & applications (01.06.2018)
    “… , artificial neural network (ANN), genetic programming (GP) and extreme learning machine (ELM)]. The calculated discharge coefficients were then compared with some experimental results …”
    Volltext
    Journal Article
  12. 12

    Alzheimer’s disease diagnosis using genetic programming based on higher order spectra features von Nasrolahzadeh, Mahda, Rahnamayan, Shahryar, Haddadnia, Javad

    ISSN: 2666-8270, 2666-8270
    Veröffentlicht: Elsevier Ltd 15.03.2022
    Veröffentlicht in Machine learning with applications (15.03.2022)
    “… ) by utilizing genetic programming (GP) as data-driven evolutionary computation based modeling …”
    Volltext
    Journal Article
  13. 13

    Machine learning and molecular descriptors enable rational solvent selection in asymmetric catalysis von Amar, Yehia, Schweidtmann, Artur M, Deutsch, Paul, Cao, Liwei, Lapkin, Alexei

    ISSN: 2041-6520, 2041-6539
    Veröffentlicht: England Royal Society of Chemistry 21.07.2019
    Veröffentlicht in Chemical science (Cambridge) (21.07.2019)
    “… Here we describe a hybrid mechanistic-machine learning approach, geared towards automated process development workflow …”
    Volltext
    Journal Article
  14. 14

    Modeling the influence of lime on the unconfined compressive strength of reconstituted graded soil using advanced machine learning approaches for subgrade and liner applications von Guo, Xinghuang, Garcia, Cesar, Andrade Valle, Alexis Ivan, Onyelowe, Kennedy, Zarate Villacres, Andrea Natali, Ebid, Ahmed M., Hanandeh, Shadi

    ISSN: 1932-6203, 1932-6203
    Veröffentlicht: United States Public Library of Science 02.04.2024
    Veröffentlicht in PloS one (02.04.2024)
    “… This present study explores the application of machine learning (ML) techniques, namely Genetic Programming (GP …”
    Volltext
    Journal Article
  15. 15

    Explainable Artificial Intelligence by Genetic Programming: A Survey von Mei, Yi, Chen, Qi, Lensen, Andrew, Xue, Bing, Zhang, Mengjie

    ISSN: 1089-778X, 1941-0026
    Veröffentlicht: New York IEEE 01.06.2023
    Veröffentlicht in IEEE transactions on evolutionary computation (01.06.2023)
    “… Genetic programming is a powerful evolutionary algorithm for machine learning. Compared with other standard machine learning models such as neural networks, the models …”
    Volltext
    Journal Article
  16. 16

    Evolutionary algorithms von Alain Petrowski, Sana Ben-Hamida

    ISBN: 1848218044, 9781848218048, 1119136415, 9781119136415
    Veröffentlicht: London ISTE 2017
    “… Evolutionary algorithms are bio-inspired algorithms based on Darwin's theory of evolution …”
    Volltext
    E-Book Buch
  17. 17

    Population Dynamics in Genetic Programming for Dynamic Symbolic Regression von Fleck, Philipp, Werth, Bernhard, Affenzeller, Michael

    ISSN: 2076-3417, 2076-3417
    Veröffentlicht: Basel MDPI AG 01.01.2024
    Veröffentlicht in Applied sciences (01.01.2024)
    “… This paper investigates the application of genetic programming (GP) for dynamic symbolic regression (SR …”
    Volltext
    Journal Article
  18. 18

    Predicting Marshall parameters of flexible pavement using support vector machine and genetic programming von Zhang, Weiguang, Khan, Adnan, Huyan, Ju, Zhong, Jingtao, Peng, Tianyi, Cheng, Hanglin

    ISSN: 0950-0618, 1879-0526
    Veröffentlicht: Elsevier Ltd 01.11.2021
    Veröffentlicht in Construction & building materials (01.11.2021)
    “… [Display omitted] •Developed SVM models to predict the Marshall parameters of base and wearing course.•Simplified expressions were derived to predict the …”
    Volltext
    Journal Article
  19. 19

    A Novel General Feature Enhancement Method Based on Genetic Programming for Improving RF Circuit Fault Diagnosis Using Machine Learning von Wu, Kunping, Long, Bing, Bu, Zhiyuan, Wang, Jingyuan, Liu, Zhen

    ISSN: 0278-081X, 1531-5878
    Veröffentlicht: New York Springer US 01.12.2025
    Veröffentlicht in Circuits, systems, and signal processing (01.12.2025)
    “… In this manuscript, a novel general feature enhancement method based on genetic programming (GP) is proposed to improve the machine learning-based RF circuit fault diagnosis …”
    Volltext
    Journal Article
  20. 20

    MACHINE LEARNING FOR THE SELF-ORGANIZATION OF DISTRIBUTED SYSTEMS IN ECONOMIC APPLICATIONS von Jerzy Balicki, Waldemar Korłub

    ISSN: 2082-677X, 2082-677X
    Veröffentlicht: University of Gdansk 01.03.2017
    Veröffentlicht in Współczesna Gospodarka (01.03.2017)
    “… For this reason, machine learning applications have been discussed because some software applications can be automatically constructed by genetic programming …”
    Volltext
    Journal Article