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Listar por autor "Herrera-Viedma, Enrique"
Mostrando ítems 41-54 de 54
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Imputation of Rainfall Data Using the Sine Cosine Function Fitting Neural Network
Chan Chiu, Po; Selamat, Ali; Krejcar, Ondrej; Kuok Kuok, King; Herrera-Viedma, Enrique; Fenza, Giuseppe (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 09/2021)Missing rainfall data have reduced the quality of hydrological data analysis because they are the essential input for hydrological modeling. Much research has focused on rainfall data imputation. However, the compatibility ... -
Managing multi-criteria group decision making environments with high number of alternatives using fuzzy ontologies
Morente-Molinera, Juan Antonio ; Kou, Gang; González-Crespo, Rubén ; 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 ... -
Mapeo científico de la Categoría «Comunicación» en WoS (1980-2013)
Montero Díaz, Julio ; Cobo, Manuel-Jesús; Gutiérrez-Salcedo, María; Segado-Boj, Francisco ; Herrera-Viedma, Enrique (Comunicar, 01/04/2018)El campo científico de la comunicación ha experimentado un enorme crecimiento a lo largo de los años, superando incluso a algunas áreas científicas consagradas. Mediante el uso de técnicas bibliométricas, podemos analizar ... -
Modelling dynamics of coronavirus disease 2019 spread for pandemic forecasting based on Simulink
Liu, Xian-Xian; Hu, Shimin; Fong, Simon James; González-Crespo, Rubén ; 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 ... -
Multilayer Framework for Botnet Detection Using Machine Learning Algorithms
Ibrahim, Wan Nur Hidayah; Anuar, Syahid; Selamat, Ali; Krejcar, Ondrej; González-Crespo, Rubén; 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 ... -
Performance and Convergence Analysis of Modified C-Means Using Jeffreys-Divergence for Clustering
Seal, Ayan; Karlekar, Aditya; Krejcar, Ondrej; Herrera-Viedma, Enrique (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 12/2021)The size of data that we generate every day across the globe is undoubtedly astonishing due to the growth of the Internet of Things. So, it is a common practice to unravel important hidden facts and understand the massive ... -
Probabilistic Forecasting Model for the COVID-19 Pandemic Based on the Composite Monte Carlo Model Integrated with Deep Learning and Fuzzy System
James Fong, Simon; Lobo Marques, João Alexandre; Li, G.; Dey, Nilanjan; González-Crespo, Rubén; Herrera-Viedma, Enrique; Bernardo Gois, F. Nauber; Xavier Neto, José (Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)There are several techniques to support simulation of time series behavior. In this chapter, the approach will be based on the Composite Monte Carlo (CMC) simulation method. This method is able to model future outcomes of ... -
Social IoT Approach to Cyber Defense of a Deep-Learning-Based Recognition System in front of Media Clones Generated by Model Inversion Attack
Khosravy, Mahdi; Nakamura, Kazuaki; Nitta, Naoko; Dey, Nilanjan; González-Crespo, Rubén; Herrera-Viedma, Enrique; Babaguchi, Noboru (IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023)Model inversion attack (MIA) is a cyber threat with an increasing alert even for deep-learning-based recognition systems (DLRSs). By targeting a DLRS under a scenario of attacker access to the model structure and parameters, ... -
Solving multi-criteria group decision making problems under environments with a high number of alternatives using fuzzy ontologies and multi-granular linguistic modelling methods
Morente-Molinera, Juan Antonio ; Kou, G; González-Crespo, Rubén ; Corchado, J M; Herrera-Viedma, Enrique (Knowledge-Based Systems, 12/2017)Classic multi-criteria group decision making models that have a high amount of alternatives are unmanageable for the experts. This is because they have to provide one value per each alternative and criteria. In this paper, ... -
The Application of Supervised and Unsupervised Computational Predictive Models to Simulate the COVID19 Pandemic
James Fong, Simon; Lobo Marques, João Alexandre; Li, G.; Dey, Nilanjan; González-Crespo, Rubén; Herrera-Viedma, Enrique; Bernardo Gois, F. Nauber; Xavier Neto, José (Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)The application of different tools for predicting COVID19 cases spreading has been widely considered during the pandemic. Comparing different approaches is essential to analyze performance and the practical support they ... -
The Comparison of Different Linear and Nonlinear Models Using Preliminary Data to Efficiently Analyze the COVID-19 Outbreak
James Fong, Simon; Lobo Marques, João Alexandre; Li, G.; Dey, Nilanjan; González-Crespo, Rubén; Herrera-Viedma, Enrique; Bernardo Gois, F. Nauber; Xavier Neto, José (Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)The COVID-19 pandemic spread generated an urgent need for computational systems to model its behavior and support governments and healthcare teams to make proper decisions. There are not many cases of global pandemics in ... -
Using clustering methods to deal with high number of alternatives on Group Decision Making
Morente-Molinera, Juan Antonio; Ríos Aguilar, Sergio ; González-Crespo, Rubén ; 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 ... -
Using Group Decision Making Methods to Extract Experts Knowledge
Morente-Molinera, Juan Antonio ; Perez, I. J.; Cabrerizo, Francisco Javier; Alonso, Sergio; Herrera-Viedma, Enrique (Advances in fuzzy logic and technology, 2018)Group Decision Making methods are interesting tools that can be used for extracting subjective information from experts that are familiar with an specific topic. Although they are typically used for carrying out an ... -
Using multi-granular fuzzy linguistic modelling methods for supervised classification learning purposes
Morente-Molinera, Juan Antonio ; Mezei, Jozsef; Carlsson, Christer; Herrera-Viedma, Enrique (2017 IEEE International conference on fuzzy systems (FUZZ-IEEE), 2017)Classification learning is a very complex process whose success and failure ratio depends on a high amount of elements. One of them is the representation mean used for the data that is employed in the process. Granularity ...