Gonzalo Nápoles

Research output

Research output per year 2010 2018 2019 2020 2021 2022 2024 2025 2025

• 66 Article
• 62 Conference contribution
• 11 Chapter
• 2 Abstract
• 8 More
  • 2 Paper
  • 2 Review article
  • 1 Book editing
  • 1 Poster
  • 1 Literature review
  • 1 Other contribution

Research output per year

Research output per year

Search results

• 2024

  A new symbolic time series representation method based on data fuzzification.

  Jastrzebska, A., Matusiewicz, Z. & Nápoles, G., 2024, ISD2024 Proceedings : Harnessing Opportunities: Reshaping ISD in the post-COVID-19 and Generative AI Era . Marcinkowski, B., Przybylek, A., Jarzębowicz, A., Iivari, N., Insfran, E., Lang, M., Linger, H. & Schneider , C. (eds.).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  Open Access

  File
  23 Downloads (Pure)

• Determining motif explanations for learning on graphs

  Soós, B., Güven, Ç., Nápoles, G. & Spronck, P., Oct 2024, (Accepted/In press) Book of Abstracts. 4 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  File

  • Machine Learning 100%
  • Learning on Graphs 100%
  • Subgraphs 100%
  • Functional Property 100%
  • Relative Frequency 100%
  7 Downloads (Pure)

• Long Short-term Cognitive Networks: An Empirical Performance Study

  Nápoles, G. & Grau, I., 2024, IEEE International Conference on Evolving and Adaptive Intelligent Systems 2024, EAIS 2024 - Proceedings. Iglesias Martinez, J. A., Baruah, R. D., Kangin, D. & De Campos Souza, P. V. (eds.). p. 1-8 8 p. (IEEE Conference on Evolving and Adaptive Intelligent Systems).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Empirical Performance 100%
  • Performance Studies 100%
  • Cognitive Networks 100%
  • Recurrent Neural Network 100%
  • Cognitive Network 100%

• Measuring Implicit Bias Using SHAP Feature Importance and Fuzzy Cognitive Maps

  Grau, I., Nápoles, G., Hoitsma, F., Koumeri, L. K. & Vanhoof, K., 2024, Intelligent Systems Conference. p. 745-764 20 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  File
  30 Downloads (Pure)

• Model Selection Using Graph Neural Networks

  Nápoles, G., Grau, I., Güven, Ç. & Salgueiro, Y., 2024, Intelligent Systems and Applications - Proceedings of the 2024 Intelligent Systems Conference IntelliSys Volume 2. Arai, K. (ed.). Springer Science and Business Media Deutschland GmbH, p. 332-347 16 p. (Lecture Notes in Networks and Systems; vol. 1066 LNNS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  Open Access

  File

  • Model Selection 100%
  • Knowledge Graph 100%
  • Graph Neural Network 100%
  • Nodes 100%
  • Adjacency 66%
  26 Downloads (Pure)

• Sparseness-Optimized Feature Importance

  Grau, I. & Nápoles, G., 2024, Explainable Artificial Intelligence. xAI 2024. Longo, L., Lapuschkin, S. & Seifert, C. (eds.). Springer Cham, p. 393-415 23 p. (Communications in Computer and Information Science; vol. 2154 CCIS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  Open Access

  File

  • Optimized Features 100%
  • Optimization Problem 100%
  • Performance Model 100%
  • Image Classification 100%
  • Numerical Simulation 100%
  19 Downloads (Pure)

• Weighted t-Distributed Stochastic Neighbor Embedding for Projection-Based Clustering

  Nápoles, G., Concepción, L., Özgöde Yigin, B., Saygili, G., Vanhoof, K. & Bello, R., 2024, Progress in Artificial Intelligence and Pattern Recognition - 8th International Congress on Artificial Intelligence and Pattern Recognition, IWAIPR 2023, Proceedings. Hernández Heredia, Y., Milián Núñez, V. & Ruiz Shulcloper, J. (eds.). p. 131-142 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 14335 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  Open Access

  • Projection-based 100%
  • T-distributed Stochastic Neighbor Embedding (t-SNE) 100%
  • High Dimensional Data Points 100%
  • Stochastics 100%
  • Data Point 100%
• 2023

  Data-Driven Multi-Objective Optimization: Analysis of Current Methods and Techniques

  Pereiras, E., Salgueiro, Y., Nápoles, G. & Rivera, M., 2023, 2023 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON). p. 1-6 6 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

• Encore Abstract: Presumably Correct Decision Sets

  Nápoles, G., Grau, I., Jastrzebska, A. & Salgueiro, Y., 2023, Pre-proceedings of the Joint International Scientific Conferences On AI And Machine Learning BNAIC/BeNeLearn 2023. TU Delft, p. 1-3 3 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  Open Access

• Feature Importance for Clustering

  Nápoles, G., Griffioen, N., Khoshrou, S. & Güven, Ç., 27 Nov 2023, Lecture Notes in Computer Science (LNCS) series. Vasconcelos, Domingues & Paredes (eds.). Springer, Vol. 14469. p. 31-45 15 p. (Lecture Notes in Computer Science ; vol. 14469).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Cluster Structure 100%
  • Cooperative Game Theory 50%
  • Clustering Methods 50%
  • Cluster Analysis 50%
  • Multiple Experiments 50%

• Presumably Correct Undersampling

  Nápoles, G. & Grau, I., 2023, Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Springer Science and Business Media Deutschland GmbH, p. 420-433 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 14469 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  Open Access

  • Classification Problem 100%
  • Undersampling 100%
  • Decision Class 100%
  • Class Label 50%
  • Generalization Ability 50%
• 2022

  Best Next Preference Prediction Based on LSTM and Multi-level Interactions

  Fuentes, I., Nápoles, G., Arco, L. & Vanhoof, K., 2022, Intelligent Systems and Applications. p. 682-699 18 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Buying 100%
  • Prediction Method 100%
  • Prediction Problems 100%
  • Customer Purchases 100%
  • Transactional Data 100%

• Explanation of Multi-Label Neural Networks with Layer-Wise Relevance Propagation

  Bello, M., Napoles, G., Vanhoof, K., Garcia, M. M. & Bello, R., 2022, 2022 International Joint Conference on Neural Networks, IJCNN 2022 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 10 p. (Proceedings of the International Joint Conference on Neural Networks; vol. 2022-July).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  Open Access

  • Neural Network 100%
  • Layer-wise Relevance Propagation 100%
  • SARS Coronavirus 100%
  • Mixed Infection 100%
  • Adaptation 33%
  1 Citation (Scopus)

• Online learning of windmill time series using Long Short-term Cognitive Networks

  Morales-Hernández, A., Nápoles, G., Jastrzebska, A., Salgueiro, Y. & Vanhoof, K., 2022, Joint International Scientific Conferences on AI and Machine Learning BNAIC/BeNeLearn 2022. 3 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  Open Access

  • Windmill 100%
  • Online Learning 100%
  • Cognitive Networks 100%
  • Neural Network 100%
  • Recurrent Neural Network Model 100%

• Semiconductor Demand Forecasting using Long Short-term Cognitive Networks

  Grau, I., de Hoop, M., Glaser, A., Nápoles, G. & Dijkman, R., 1 Nov 2022, Proceedings of the 34th Benelux Conference on Artificial Intelligence and 31st Belgian-Dutch Conference on Machine Learning, BNAIC/BeNeLearn 2022. Antwerpen University, p. 1-13 13 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Statistical Technique 100%
  • Supply Chain 100%
  • Machine Learning Technique 100%
  • Interpretability 100%
  • Multivariate Time Series 100%

• Skipped Nonsynaptic Backpropagation for Interval-valued Long-term Cognitive Networks

  Frias, M., Nápoles, G., Filiberto, Y., Bello, R. & Vanhoof, K., 2022, Mexican International Conference on Artificial Intelligence. p. 3-14 12 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  Open Access

  • Nonsynaptic 100%
  • Long-term Cognitive Networks 100%
  • Backpropagation 100%
  • Modeling and Simulation 100%
  • Learning Algorithm 100%
• 2021

  Bias Quantification for Protected Features in Pattern Classification Problems

  Koutsoviti Koumeri, L. & Nápoles, G., 2021, Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Tavares, J. M. R. S., Papa, J. P. & González Hidalgo, M. (eds.). Cham: Springer International Publishing, p. 351-360 10 p. (Lecture Notes in Computer Science; vol. 12702).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Classification Problem 100%
  • Prediction Model 100%
  • Pattern Classification 100%
  • Rough Set Theory 100%
  • Distance Function 100%

• Evolving Recurrent Neural Networks for Pattern Classification

  Nápoles, G., 2021, Intelligent Systems and Applications. Arai, K., Kapoor, S. & Bhatia, R. (eds.). Springer International Publishing, p. 388-398 11 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Recurrent Neural Network 100%
  • Pattern Classification 100%
  • Black-box Classifier 100%
  • Popular 50%
  • Numerical Simulation 50%

• Fuzzy Cognitive Maps for Impact Assessment in Psychological Research: Case Study of Psychological Well-being

  Farahani, H., Nápoles, G. & Azadfallah, P., 2021, Conference: 3th International Conference on Modern Approach in Humanities and Social Sciences (ICMHS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

• Layer-Wise Relevance Propagation in Multi-label Neural Networks to Identify COVID-19 Associated Coinfections

  Bello, M., Aguilera, Y., Nápoles, G., García, M. M., Bello, R. & Vanhoof, K., 2021, Progress in Artificial Intelligence and Pattern Recognition - 7th International Workshop on Artificial Intelligence and Pattern Recognition, IWAIPR 2021, Proceedings. Hernández Heredia, Y., Milián Núñez, V. & Ruiz Shulcloper, J. (eds.). Springer Science and Business Media Deutschland GmbH, p. 3-12 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13055 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Neural Network 100%
  • COVID-19 100%
  • Co-infection 100%
  • Layer-wise Relevance Propagation 100%
  • Infection 100%
  4 Citations (Scopus)

• Nonsynaptic Backpropagation Learning of Interval-valued Long-term Cognitive Networks

  Frias, M., Napoles, G., Vanhoof, K., Filiberto, Y. & Bello, R., 18 Jul 2021, IJCNN 2021 - International Joint Conference on Neural Networks, Proceedings. Institute of Electrical and Electronics Engineers Inc., (Proceedings of the International Joint Conference on Neural Networks; vol. 2021-July).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Nonsynaptic 100%
  • Long-term Cognitive Networks 100%
  • Backpropagation Learning 100%
  • Modeling and Simulation 100%
  • Learning Algorithm 100%
  2 Citations (Scopus)

• On the performance of the nonsynaptic backpropagation for training long-term cognitive networks

  Nápoles, G., Grau, I., Concepción, L. & Salgueiro, Y., 2021, 11th International Conference of Pattern Recognition Systems, ICPRS 2021. CP773 ed. Institution of Engineering and Technology, p. 25-30 6 p. (IET Conference Publications; vol. 2021, no. CP773).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Nonsynaptic 100%
  • Long-term Cognitive Networks 100%
  • Backpropagation 100%
  • Recurrent Neural Network 100%
  • Backpropagation Algorithm 100%
• 2020

  Customer Interaction Networks Based on Multiple Instance Similarities

  Fuentes, I., Nápoles, G., Arco, L. & Vanhoof, K., 2020, Business Information Systems. p. 279-290 12 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Network Applications 100%
  • Interaction Network 100%
  • Customer Interaction 100%
  • Multiple Instances 100%
  • Instance Similarity 100%

• Fast k-Fuzzy-Rough Cognitive Networks

  Nápoles, G., Goossens, W., Moesen, Q. & Mosquera, C., Jul 2020, 2020 International Joint Conference on Neural Networks, IJCNN 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 9207575. (Proceedings of the International Joint Conference on Neural Networks).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Fuzzy Rough 100%
  • Rough Cognitive Networks 100%
  • Processing Time 100%
  • Noisy Environment 100%
  • Neural Network 50%
  2 Citations (Scopus)

• Feature and Label Association Based on Granulation Entropy for Deep Neural Networks

  Bello, M., Nápoles, G., Sánchez, R., Vanhoof, K. & Bello, R., 2020, Rough Sets. Bello, R., Miao, D., Falcon, R., Nakata, M., Rosete, A. & Ciucci, D. (eds.). Cham: Springer International Publishing, p. 225-235 11 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Number of Parameters 100%
  • Deep Neural Network 100%
  • Neural Network 100%
  • Model Use 50%
  • Redundancy 50%

• Fuzzy Cognitive Maps: A Business Intelligence Discussion

  Nápoles, G., Van Houdt, G., Laghmouch, M., Goossens, W., Moesen, Q. & Depaire, B., 2020, Intelligent Decision Technologies 2019. p. 89-98 10 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Business Intelligence 100%
  • Fuzzy Cognitive Maps 100%
  • Problem Domain 100%
  • Computational Modeling 50%
  • Case Study 50%

• Fuzzy Cognitive Modeling: Theoretical and Practical Considerations

  Nápoles, G., Salmeron, J. L., Froelich, W., Falcon, R., Léon, M., Vanhoenshoven, F., Bello, R. & Vanhoof, K., 2020, Intelligent Decision Technologies 2019. p. 77-87 11 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Fuzzy Cognitive Maps 100%
  • Fuzzy Cognitive Model 100%
  • Fuzzy Cognitive Map 100%
  • Cognitive Map 100%
  • Well-defined 20%

• Multi-agent-Based Decision Support Systems in Smart Microgrids

  Salgueiro, Y., Rivera, M. & Nápoles, G., 2020, Intelligent Decision Technologies 2019. p. 123-132 10 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Decision Support System 100%
  • Smart Microgrid 100%
  • Microgrid 100%
  • Multi-agent Based 100%
  • Support System 100%

• On the Behavior of Fuzzy Grey Cognitive Maps

  Concepción, L., Nápoles, G., Bello, R. & Vanhoof, K., 2020, Rough Sets. Bello, R., Miao, D., Falcon, R., Nakata, M., Rosete, A. & Ciucci, D. (eds.). Cham: Springer International Publishing, p. 462-476 15 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Fixed Points 100%
  • Sufficient Condition 100%
  • Neural Network 100%
  • Causal Relation 100%
  • World Problems 100%

• Outliers Detection in Multi-label Datasets

  Bello, M., Nápoles, G., Morera, R., Vanhoof, K. & Bello, R., 2020, Advances in Soft Computing - 19th Mexican International Conference on Artificial Intelligence, MICAI 2020, Proceedings. Martínez-Villaseñor, L., Ponce, H., Herrera-Alcántara, O. & Castro-Espinoza, F. A. (eds.). Springer Science and Business Media Deutschland GmbH, p. 65-75 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12468 LNAI).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Outlier Detection 100%
  • Multi-label Data 100%
  • Electronic Commerce 33%
  • Criminal Activity 33%
  • Synthetic Data 33%
  4 Citations (Scopus)

• Rough Net Approach for Community Detection Analysis in Complex Networks

  Fuentes, I., Pina, A., Nápoles, G., Arco, L. & Vanhoof, K., 2020, Rough Sets. p. 401-415 15 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Community Structure 100%
  • Dynamic Networks 100%
  • Complex Networks 100%
  • Rough Set Theory 100%
  • Community Detection Analysis 100%

• Symbolic Explanation Module for Fuzzy Cognitive Map-Based Reasoning Models

  Hoitsma, F., Knoben, A., Espinosa, M. L. & Nápoles, G., 2020, Artificial Intelligence XXXVII. p. 21-34 14 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Map-based 100%
  • Fuzzy Cognitive Maps 100%
  • Symbolic Explanations 100%
  • Reasoning Model 100%
  • Interpretability 100%
• 2019

  A Preliminary Study on Symbolic Fuzzy Cognitive Maps for Pattern Classification

  Frias, M., Nápoles, G., Filiberto, Y., Bello, R. & Vanhoof, K., 2019, Applied Computer Sciences in Engineering. Figueroa-García, J. C., Duarte-González, M., Jaramillo-Isaza, S., Orjuela-Cañon, A. D. & Díaz-Gutierrez, Y. (eds.). Cham: Springer International Publishing, p. 285-295 11 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Fuzzy Cognitive Maps 100%
  • Pattern Classification 100%
  • Interpretability 50%
  • Causal Relationship 50%
  • Performance Model 50%

• Fuzzy-Rough Cognitive Networks: Building Blocks and Their Contribution to Performance

  Vanloffelt, M., Nápoles, G. & Vanhoof, K., 2019, 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA). p. 922-928 7 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

• Methods to Edit Multi-label Training Sets Using Rough Sets Theory

  Bello, M., Nápoles, G., Vanhoof, K. & Bello, R., 2019, Proceedings of the International Joint Conference on Rough Sets (IJCRS 2019).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

• Multi-objective Metaheuristics’ Challenges in the Optimization of Microgrids Planning and Management

  Salgueiro, Y., Rivera, M. & Nápoles, G., 2019, Proceedings of the 2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies. p. 1-6 6 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

• Prototypes Generation from Multi-label Datasets Based on Granular Computing

  Bello, M., Nápoles, G., Vanhoof, K. & Bello, R., 2019, Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Nyström, I., Hernández Heredia, Y. & Milián Núñez, V. (eds.). Cham: Springer International Publishing, p. 142-151 10 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Multi-label Data 100%
  • Prototype Generation 100%
  • Granular Computing 100%
  • Generation Method 50%
  • Experimental Result 50%

• Reduction methods for multi-label datasets based on Granular Computing

  Bello, M., Nápoles, G., Vanhoof, K. & Bello, R., 2019, Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

• Synaptic Learning of Long-Term Cognitive Networks with Inputs

  Sosa, R., Alfonso, A., Nápoles, G., Bello, R., Vanhoof, K. & Nowé, A., 2019, Proceedings of the 2019 International Joint Conference on Neural Networks (IJCNN). p. 1-8 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
• 2018

  Expanding MLkNN Using Extended Rough Set Theory

  Pérez, G., Bello, M., Nápoles, G., García, M. M., Bello, R. & Vanhoof, K., 2018, Progress in Artificial Intelligence and Pattern Recognition. Hernández Heredia, Y., Milián Núñez, V. & Ruiz Shulcloper, J. (eds.). Cham: Springer International Publishing, p. 247-254 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • K-nearest 100%
  • Multi-label Classification 100%
  • Multi-label K-nearest Neighbor 100%
  • Extended Rough Set Theory 100%
  • Rough Set Theory 100%

• Forecasting Social Security Revenues in Jordan Using Fuzzy Cognitive Maps

  Alghzawi, A. Z., Nápoles, G., Sammour, G. & Vanhoof, K., 2018, Intelligent Decision Technologies 2017. Czarnowski, I., Howlett, R. J. & Jain, L. C. (eds.). Cham: Springer International Publishing, p. 246-254 9 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Social Security 100%
  • Jordan 100%
  • Fuzzy Cognitive Maps 100%
  • Neural Network 100%
  • Expert Knowledge 100%

• Fuzzy Cognitive Maps Employing ARIMA Components for Time Series Forecasting

  Vanhoenshoven, F., Nápoles, G., Bielen, S. & Vanhoof, K., 2018, Intelligent Decision Technologies 2017. Czarnowski, I., Howlett, R. J. & Jain, L. C. (eds.). Cham: Springer International Publishing, p. 255-264 10 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Autoregressive Integrated Moving Average (ARIMA) 100%
  • Fuzzy Cognitive Maps 100%
  • Time Series Forecasting 100%
  • Auto Regressive Integrated Moving Average 100%
  • Time Series Prediction 100%

• Fuzzy Cognitive Maps Reasoning with Words Based on Triangular Fuzzy Numbers

  Frias, M., Filiberto, Y., Nápoles, G., García-Socarrás, Y., Vanhoof, K. & Bello, R., 2018, Advances in Soft Computing. Castro, F., Miranda-Jiménez, S. & González-Mendoza, M. (eds.). Cham: Springer International Publishing, p. 197-207 11 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Fuzzy Cognitive Maps 100%
  • Word-based 100%
  • Triangular Fuzzy number 100%
  • Interpretability 100%
  • Reasoning Mechanism 100%

• Performance Analysis of Granular versus Traditional Neural Network Classifiers: Preliminary Results

  Felix, G., Nápoles, G., Falcon, R., Bello, R. & Vanhoof, K., 2018, Proceedings of 2018 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA). p. 1-6 6 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
• 2017

  Fuzzy Cognitive Maps Tool for Scenario Analysis and Pattern Classification

  Nápoles, G., Leon, M., Grau, I. & Vanhoof, K., 2017, Proceedings of the 2017 IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI). p. 644-651 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
• 2016

  Analyzing the impact of the adaptive clearing mechanism on algorithm accuracy in Variable Mesh Optimization

  Vanhoenshoven, F., Nápoles, G., Creemers, M., León, M. & Vanhoof, K., 2016, Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence (SSCI). p. 1-8 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

• Detecting malicious URLs using machine learning techniques

  Vanhoenshoven, F., Nápoles, G., Falcon, R., Vanhoof, K. & Köppen, M., 2016, Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence (SSCI). p. 1-8 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

• Partitive granular Cognitive Maps to graded multilabel classification

  Nápoles, G., Falcon, R., Papageorgiou, E., Bello, R. & Vanhoof, K., 2016, Proceedings of the 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). p. 1363-1370 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
• 2015

  A computational tool for simulation and learning of Fuzzy Cognitive Maps

  Nápoles, G., Grau, I., Bello, R., León, M., Vanhoof, K. & Papageorgiou, E., 2015, Proceedings of the 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). p. 1-8 8 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

• Aggregation of Partial Rankings - An Approach Based on the Kemeny Ranking Problem

  Nápoles, G., Dikopoulou, Z., Papageorgiou, E., Bello, R. & Vanhoof, K., 2015, Advances in Computational Intelligence. Rojas, I., Joya, G. & Catala, A. (eds.). Cham: Springer International Publishing, p. 343-355 13 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

  • Partial Ranking 100%
  • Kemeny Ranking Problem 100%
  • Pareto-optimality 100%
  • Ant Colony Optimization 100%
  • Minimal Distance 100%