Papers published in Journals (J. Alcalá-Fdez)

Number of Results: 46

Jump to Year: 2024, 2023, 2022, 2021, 2020, 2019, 2018, 2017, 2016, 2015, 2014, 2013, 2012, 2011, 2010, 2009, 2008, 2007, 2006

Jump to Graph

2024 (1)

• [3100] A. Torres-Martos, A. Anguita-Ruiz, M. Bustos-Aibar, A. Ramírez-Mena, M. Arteaga, G. Bueno, R. Leis, C.M. Aguilera, R. Alcalá, J. Alcalá-Fdez. Multiomics and eXplainable artificial intelligence for decision support in insulin resistance early diagnosis: A pediatric population-based longitudinal study. Artificial Intelligence in Medicine 156 (2024) 102962. doi: 10.1016/j.artmed.2024.102962
  

2023 (5)

• [3030] Á. Torres-Martos, M. Bustos-Aibar, A. Ramírez-Mena, S. Cámara-Sánchez, A. Anguita-Ruiz, R. Alcalá, C.M. Aguilera, J. Alcalá-Fdez. Omics Data Preprocessing for Machine Learning: A Case Study in Childhood Obesity. Genes 14:2 (2023) 248. doi: 10.3390/genes14020248
  
• [3043] C. Biedma-Rdguez, M.J. Gacto, A. Anguita-Ruiz, R. Alcalá, C.M. Aguilera, J. Alcalá-Fdez. Learning positive-negative rule-based fuzzy associative classifiers with a good trade-off between complexity and accuracy. Fuzzy Sets and Systems 465 (2023) 108511. doi: 10.1016/j.fss.2023.03.014
  
• [3050] M. Bustos-Aibar, C.M. Aguilera, J. Alcalá-Fdez, F.J. Ruiz-Ojeda, J. Plaza, A. Plaza-Florido, I. Tofe, M. Gil-Campos, M.J. Gacto, A. Anguita-Ruiz. Shared gene expression signatures between visceral adipose and skeletal muscle tissues are associated with cardiometabolic traits in boys with obesity. Computers in Biology and Medicine 163 (2023) 107085. doi: 10.1016/j.compbiomed.2023.107085
  
• [3053] A. Ramírez-Mena, E. Andrés-León, M.J. Alvarez-Cubero, A. Anguita-Ruiz, L.J. Martinez-Gonzalez, J. Alcalá-Fdez. Explainable artificial intelligence to predict and identify prostate cancer tissue by gene expression. Computer Methods and Programs in Biomedicine 240 (2023) 107719. doi: https://doi.org/10.1016/j.cmpb.2023.107719
  
• [3054] M. Arteaga, M.J. Gacto, M. Galende, J. Alcalá-Fdez, R. Alcalá. Enhancing soft computing techniques to actively address imbalanced regression problems. Expert Systems with Applications 234 (2023) 121011. doi: 10.1016/j.eswa.2023.121011
  

2022 (2)

• [2961] A. Segura-Delgado, A. Anguita-Ruiz, R. Alcalá, J. Alcalá-Fdez. Mining high average-utility sequential rules to identify high-utility gene expression sequences in longitudinal human studies. Expert Systems with Applications 193 (2022) 116411. doi: 10.1016/j.eswa.2021.116411
  
• [2998] C. Biedma-Rdguez, M.J. Gacto, A. Anguita-Ruiz, J. Alcalá-Fdez, R. Alcalá. Transparent but Accurate Evolutionary Regression Combining New Linguistic Fuzzy Grammar and a Novel Interpretable Linear Extension. International Journal of Fuzzy Systems 24 (2022) 3082–3103. doi: 10.1007/s40815-022-01324-w
  

2021 (1)

• [2929] A. Anguita-Ruiz; M. Bustos-Aibar; J. Plaza-Díaz; A. Mendez-Gutierrez; J. Alcalá-Fdez; C.M. Aguilera; F.J. Ruiz-Ojeda. Omics Approaches in Adipose Tissue and Skeletal Muscle Addressing the Role of Extracellular Matrix in Obesity and Metabolic Dysfunction. International Journal of Molecular Sciences 22:5 (2021) 2756. doi: 10.3390/ijms22052756
  

2020 (3)

• [2799] A. Anguita-Ruiz, A. Segura-Delgado, R. Alcalá, C.M. Aguilera, J. Alcalá-Fdez. eXplainable Artificial Intelligence (XAI) for the identification of biologically relevant gene expression patterns in longitudinal human studies, insights from obesity research. PLoS Computational Biology 16:4 (2020) 1-34. doi: 10.1371/journal.pcbi.1007792
  
• [2800] A. Segura-Delgado, M.J. Gacto, R. Alcalá, J. Alcalá-Fdez. Temporal association rule mining: An overview considering the time variable as an integral or implied component. Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery 10:4 (2020) e1367. doi: 10.1002/widm.1367
  
• [2960] A. Anguita-Ruiz, E.M. González-Gil, A.I. Rupérez, F.J. Llorente-Cantarero, B. Pastor-Villaescusa, J. Alcalá-Fdez, L.A. Moreno, Á. Gil, M. Gil-Campos, G. Bueno, R. Leis, C.M. Aguilera. Evaluation of the Predictive Ability, Environmental Regulation and Pharmacogenetics Utility of a BMI-Predisposing Genetic Risk Score during Childhood and Puberty. Journal of Clinical Medicine 9:6 (2020) 1705. doi: 10.3390/jcm9061705
  

2019 (2)

• [2640] J.M. Soto-Hidalgo, A. Vitiello, J.M. Alonso, G. Acampora, J. Alcalá-Fdez. Design of Fuzzy Controllers for Embedded Systems With JFML. International Journal of Computational Intelligence Systems 12:1 (2019) 204-214. doi: 10.2991/ijcis.2019.125905646
  
• [2695] M.J. Gacto, J.M. Soto-Hidalgo, J. Alcalá-Fdez, R. Alcalá. Experimental Study on 164 Algorithms Available in Software Tools for Solving Standard Non-Linear Regression Problems. IEEE Access 7 (2019) 108916-108939. doi: 10.1109/ACCESS.2019.2933261
  

2018 (3)

• [2422] R. Alcalá, M.J. Gacto, J. Alcalá-Fdez. Evolutionary data mining and applications: A revision on the most cited papers from the last 10 years (2007-2017). Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery 8:2 (2018) 1-17. doi: 10.1002/widm.1239
  
• [2462] D. Martín, M. Martínez-Ballesteros, D. García-Gil, J. Alcalá-Fdez, J.C. Riquelme-Santos, F. Herrera. MRQAR: a generic MapReduce framework to discover Quantitative Association Rules in Big Data problems. Knowledge-Based Systems 153 (2018) 176-192. doi: 10.1016/j.knosys.2018.04.037
  
• [2505] J.M. Soto-Hidalgo, J.M. Alonso, G. Acampora, J. Alcalá-Fdez. JFML: A Java Library to Design Fuzzy Logic Systems According to the IEEE Std 1855-2016. IEEE Access 6 (2018) 54952-54964. doi: 10.1109/ACCESS.2018.2872777
  

2017 (2)

• [2307] J. Alcalá-Fdez, R. Alcalá, S. González, Y. Nojima, S. García. Evolutionary Fuzzy Rule-Based Methods for Monotonic Classification. IEEE Transactions on Fuzzy Systems 25:6 (2017) 1376-1390. doi: 10.1109/TFUZZ.2017.2718491
  
• [2322] I. Triguero, S. González, J.M. Moyano, S. García, J. Alcalá-Fdez, J. Luengo, A. Fernández, M.J. del Jesús, L. Sánchez and F. Herrera. KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining. International Journal of Computational Intelligence Systems 10 (2017) 1238-1249.
  

2016 (2)

• [1920] J. Alcalá-Fdez, J.M. Alonso. A Survey of Fuzzy Systems Software: Taxonomy, Current Research Trends and Prospects. IEEE Transactions on Fuzzy Systems 24:1 (2016) 40-56. doi: 10.1109/TFUZZ.2015.2426212
  COMPLEMENTARY MATERIAL to the paper: software, bibliography, events, etc
  
  
• [2079] D. Martin, J. Alcalá-Fdez, A. Rosete, F. Herrera. NICGAR: a Niching Genetic Algorithm to Mine a Diverse Set of Interesting Quantitative Association Rules. Information Sciences 355-356 (2016) 208-228. doi: 10.1016/j.ins.2016.03.039
  COMPLEMENTARY MATERIAL to the paper: datasets, experimental results, etc
  
  

2015 (1)

• [1832] A. Palacios, J.L. Palacios, L. Sánchez, J. Alcalá-Fdez. Genetic Learning of the Membership Functions for Mining Fuzzy Association Rules from Low Quality Data. Information Sciences 295 (2015) 358-378. doi: 10.1016/j.ins.2014.10.027
  

2014 (2)

• [1673] D. Martín, A. Rosete, J. Alcalá-Fdez, F. Herrera. QAR-CIP-NSGA-II: A New Multi-Objective Evolutionary Algorithm to Mine Quantitative Association Rules. Information Sciences 258 (2014) 1-28. doi: 10.1016/j.ins.2013.09.009
  
• [1674] D. Martín, A. Rosete, J. Alcalá-Fdez, F. Herrera. A New Multi-Objective Evolutionary Algorithm for Mining a Reduced Set of Interesting Positive and Negative Quantitative Association Rules. IEEE Transactions on Evolutionary Computation 18:1 (2014) 54-69. doi: 10.1109/TEVC.2013.2285016
  

2013 (1)

• [1644] P. Cingolani, J. Alcalá-Fdez. jFuzzyLogic: a Java library to design fuzzy logic controllers according to the standard for fuzzy control programming. International Journal of Computational Intelligence Systems 6:1 (2013) 61-75. doi: 10.1080/18756891.2013.818190
  

2012 (3)

• [1336] F. Chávez, F. Fernández, R. Alcalá, J. Alcalá-Fdez, G. Olague, F. Herrera. Hybrid Laser Pointer Detection Algorithm Based on Template Matching and Fuzzy Rule-Based Systems for Domotic Control in Real Home Enviroments. Applied Intelligence 36:2 (2012) 407-423. doi: 10.1007/s10489-010-0268-6
  
• [1398] A. Palacios, M.J. Gacto, J. Alcalá-Fdez. Mining Fuzzy Association Rules from Low Quality Data. Soft Computing 16:5 (2012) 883-901. doi: 10.1007/s00500-011-0775-3
  
• [1506] J.L. Aznarte M., J. Alcalá-Fdez, A. Arauzo, J.M. Benítez. Financial Time Series Forecasting with a Bio-inspired Fuzzy Model. Expert Systems with Applications 39:16 (2012) 12302–12309. doi: 10.1016/j.eswa.2012.02.135
  

2011 (3)

• [1277] J. Alcalá-Fdez, A. Fernandez, J. Luengo, J. Derrac, S. García, L. Sánchez, F. Herrera. KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework. Journal of Multiple-Valued Logic and Soft Computing 17:2-3 (2011) 255-287.
  SOFTWARE associated to the paper here
  
  
• [1279] J.L. Aznarte M., J. Alcalá-Fdez, A. Arauzo, J.M. Benítez. Fuzzy autoregressive rules: Towards linguistic time series modeling. Econometric Reviews 30:6 (2011) 609–631. doi: 10.1080/07474938.2011.553569
  
• [1402] J. Alcalá-Fdez, R. Alcalá, F. Herrera. A Fuzzy Association Rule-Based Classification Model for High-Dimensional Problems with Genetic Rule Selection and Lateral Tuning. IEEE Transactions on Fuzzy Systems 19:5 (2011) 857-872. doi: 10.1109/TFUZZ.2011.2147794
  

2010 (2)

• [1071] M. Mucientes, J. Alcalá-Fdez, R. Alcalá, J. Casillas. A case study for learning behaviors in mobile robotics by evolutionary fuzzy systems. Expert Systems With Applications 37:2 (2010) 1471–1493. doi: 10.1016/j.eswa.2009.06.095
  
• [1186] J. Alcalá-Fdez, N. Flugy-Pape, A. Bonarini, F. Herrera. Analysis of the Effectiveness of the Genetic Algorithms based on Extraction of Association Rules. Fundamenta Informaticae 98:1 (2010) 1001-1014.
  

2009 (4)

• [0758] J. Alcalá-Fdez, L. Sánchez, S. García, M.J. del Jesus, S. Ventura, J.M. Garrell, J. Otero, C. Romero, J. Bacardit, V.M. Rivas, J.C. Fernández, F. Herrera. KEEL: A Software Tool to Assess Evolutionary Algorithms for Data Mining Problems. Soft Computing 13:3 (2009) 307-318. doi: 10.1007/s00500-008-0323-y
  SOFTWARE associated to the paper
  
  
• [0650] M. Mucientes, R. Alcalá, J. Alcalá-Fdez, J. Casillas. Learning Weighted Linguistic Rules to Control an Autonomous Robot. International Journal of Intelligent Systems 24:3 (2009) 226–251. doi: 10.1002/int.20334
  
• [0671] R. Alcalá, J. Alcalá-Fdez, M.J. Gacto, F. Herrera. Improving Fuzzy Logic Controllers Obtained by Experts: A Case Study in HVAC Systems. Applied Intelligence 31:1 (2009) 15-30. doi: 10.1007/s10489-007-0107-6
  
• [0838] J. Alcalá-Fdez, R. Alcalá, M.J. Gacto, F. Herrera. Learning the Membership Function Contexts for Mining Fuzzy Association Rules by Using Genetic Algorithms. Fuzzy Sets and Systems 160:7 (2009) 905-921. doi: 10.1016/j.fss.2008.05.012
  

2008 (2)

• [0446] S. Alonso, F. Chiclana, F. Herrera, E. Herrera-Viedma, J. Alcalá-Fdez, C. Porcel. A Consistency-Based Procedure to Estimate Missing Pairwise Preference Values. International Journal of Intelligent Systems 23:2 (2008) 155-175. doi: 10.1002/int.20262
  
• [0685] J. Otero, L. Sánchez, J. Alcalá-Fdez. Fuzzy-genetic optimization of the parameters of a low cost system for the optical measurement of several dimensions of vehicles. Soft Computing 12:8 (2008) 751–764. doi: 10.1007/s00500-007-0234-3
  

2007 (6)

• [0344] R. Alcalá, J. Alcalá-Fdez, J. Casillas, O. Cordón, F. Herrera. Local Identification of Prototypes for Genetic Learning of Accurate TSK Fuzzy Rule-Based Systems. International Journal of Intelligent Systems 22:9 (2007) 909-941. doi: 10.1002/int.20232
  
• [0346] J. Alcalá-Fdez, F. Herrera, F. Márquez, A. Peregrín. Increasing Fuzzy Rules Cooperation Based on Evolutionary Adaptive Inference Systems. International Journal of Intelligent Systems 22:9 (2007) 1035-1064. doi: 10.1002/int.20237
  
• [0651] R. Alcalá, M.J. Gacto, F. Herrera, J. Alcalá-Fdez. A Multi-objective Genetic Algorithm for Tuning and Rule Selection to Obtain Accurate and Compact Linguistic Fuzzy Rule-Based Systems. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 15:5 (2007) 539–557. doi: 10.1142/S0218488507004868
  
• [0556] R. Alcalá, J. Alcalá-Fdez, M.J. Gacto, F. Herrera. Rule Base Reduction and Genetic Tuning of Fuzzy Systems based on the Linguistic 3-Tuples Representation. Soft Computing 11:5 (2007) 401-419. doi: 10.1007/s00500-006-0106-2
  
• [0572] R. Alcalá, J. Alcalá-Fdez, F. Herrera, J. Otero. Genetic Learning of Accurate and CompactFuzzy Rule Based Systems Based on the 2-Tuples LinguisticRepresentation. International Journal of Approximate Reasoning 44:1 (2007) 45-64. doi: 10.1016/j.ijar.2006.02.007
  
• [0598] R. Alcalá, J. Alcalá-Fdez, F. Herrera. A Proposal for the Genetic Lateral Tuning of Linguistic Fuzzy Systems and its Interaction with Rule Selection. IEEE Transactions on Fuzzy Systems 15:4 (2007) 616-635. doi: 10.1109/TFUZZ.2006.889880
  

2006 (1)

• [0343] R. Alcalá, J. Alcalá-Fdez, J. Casillas, O. Cordón, F. Herrera. Hybrid learning models to get the interpretability-accuracy trade-off in Fuzzy Modelling. Soft Computing 10:9 (2006) 717-734. doi: 10.1007/s00500-005-0002-1