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    Managing multi-criteria group decision making environments with high number of alternatives using fuzzy ontologies 

    Morente-Molinera, Juan Antonio (1); Kou, Gang; González-Crespo, Rubén (1); Corchado, J M; Herrera-Viedma, Enrique (Frontiers in Artificial Intelligence and Applications, 2018)
    The high amount of information that modern multi-criteria group decision making environments must handle requires the development of novel methods. These methods should be able to work with high amounts of alternatives ...

    Using clustering methods to deal with high number of alternatives on Group Decision Making 

    Morente-Molinera, Juan Antonio; Ríos Aguilar, Sergio (1); González-Crespo, Rubén (1); Herrera-Viedma, Enrique (7th International Conference on Information Technology and Quantitative Management (ITQM), 2019)
    Novel Group Decision Making methods and Web 2.0 have augmented the quantity of data that experts have to discuss about. Nevertheless, experts are only capable of dealing with a reduced set of information. In this paper, a ...

    Multilayer Framework for Botnet Detection Using Machine Learning Algorithms 

    Ibrahim, Wan Nur Hidayah; Anuar, Syahid; Selamat, Ali; Krejcar, Ondřej; González-Crespo, Rubén (1); Herrera-Viedma, Enrique; Fujita, Hamido (IEEE Access, 2021)
    A botnet is a malware program that a hacker remotely controls called a botmaster. Botnet can perform massive cyber-attacks such as DDOS, SPAM, click-fraud, information, and identity stealing. The botnet also can avoid being ...

    A new SEAIRD pandemic prediction model with clinical and epidemiological data analysis on COVID-19 outbreak 

    Liu, Xian-Xian; Fong, Simon James; Dey, Nilanjan; González-Crespo, Rubén (1); Herrera-Viedma, Enrique (Applied intelligence, 2021)
    Measuring the spread of disease during a pandemic is critically important for accurately and promptly applying various lockdown strategies, so to prevent the collapse of the medical system. The latest pandemic of COVID-19 ...

    Modelling dynamics of coronavirus disease 2019 spread for pandemic forecasting based on Simulink 

    Liu, Xian-Xian; Hu, Shimin; Fong, Simon James; González-Crespo, Rubén (1); Herrera-Viedma, Enrique (Physical biology, 2021)
    In this paper, we demonstrate the application of MATLAB to develop a pandemic prediction system based on Simulink. The susceptible-exposed-asymptomatic but infectious-symptomatic and infectious (severe infected population ...

    Alzheimer's Patient Analysis Using Image and Gene Expression Data and Explainable-AI to Present Associated Genes 

    Kamal, M.S; Northcote, A; Chowdhury, L; Dey, Nilanjan; González-Crespo, Rubén (1); Herrera-Viedma, Enrique (Institute of Electrical and Electronics Engineers Inc., 2021)
    There are more than 10 million new cases of Alzheimer's patients worldwide each year, which means there is a new case every 3.2 s. Alzheimer's disease (AD) is a progressive neurodegenerative disease and various machine ...

    Enhancing big data feature selection using a hybrid correlation-based feature selection 

    Mohamad, Masurah; Selamat, Ali; Krejcar, Ondrej; González-Crespo, Rubén (1); Herrera-Viedma, Enrique; Fujita, Hamido (2021)
    This study proposes an alternate data extraction method that combines three well-known feature selection methods for handling large and problematic datasets: the correlation-based feature selection (CFS), best first search ...

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