An Adaptable Time-Delay Neural Network to Predict the Spanish Economic Indebtedness. - Manuel P. Cuéllar; Waldo Fajardo; Maria del Carmen Pegalajar Jiménez; Ramón Pérez-Pérez; M. Angeles Gonzales Navarro (ICEIS (2), 2004)

A Comparative Study of Evolutionary Algorithms for Training Elman Recurrent Neural Networks to Predict Autonomous Indebtedness. - Manuel P. Cuéllar; A. Navarro; Maria del Carmen Pegalajar Jiménez; Ramón Pérez-Pérez (ICEIS (2), 2004)

An Information System to Perform Services Remotely from a Web Browser. - Manuel P. Cuéllar; Miguel Delgado 001; Waldo Fajardo; Ramón Pérez-Pérez (ICEIS (2), 2005)

An Application of Non-Linear Programming to Train Recurrent Neural Networks in Time Series Prediction Problems. - Manuel P. Cuéllar; Miguel Delgado 001; Maria del Carmen Pegalajar Jiménez (ICEIS (2), 2005)

Memetic evolutionary training for recurrent neural networks: an application to time-series prediction. - Miguel Delgado 001; Maria del Carmen Pegalajar Jiménez; Manuel P. Cuéllar (Expert Syst. J. Knowl. Eng., 2006)

Problems and Features of Evolutionary Algorithms to Build Hybrid Training Methods for Recurrent Neural Networks. - Manuel P. Cuéllar; Miguel Delgado 001; Maria del Carmen Pegalajar Jiménez (ICEIS (2), 2007)

Topology Optimization and Training of Recurrent Neural Networks with Pareto-Based Multi-objective Algorithms: A Experimental Study. - Manuel P. Cuéllar; Miguel Delgado 001; Maria del Carmen Pegalajar Jiménez (IWANN, 2007)

Multiobjective Hybrid Optimization and Training of Recurrent Neural Networks. - Miguel Delgado 001; Manuel P. Cuéllar; Maria del Carmen Pegalajar Jiménez (IEEE Trans. Syst. Man Cybern. Part B, 2008)

A.I.P.O.: Aula Interactiva para Prácticas con Ordenador. - Manuel P. Cuéllar; Fernando Berzal Galiano; Pedro González; Nicolás Marín; Javier Martinez-Baena; Ignacio Requena (Rev. Iberoam. de Tecnol. del Aprendiz., 2009)

Multi-Objective Training of Neural Networks. - Manuel P. Cuéllar; Miguel Delgado 001; Maria del Carmen Pegalajar Jiménez (Encyclopedia of Artificial Intelligence, 2009)

An Estimator Update Scheme for Large Teams of Learning Automata. - Manuel P. Cuéllar; María Ros; Miguel Delgado 001; Maria-Amparo Vila (DCAI, 2011)

Linguistic summarization of long-term trends for understanding change in human behavior. - María Ros; Manuel Pegalajar Cuéllar; Miguel Delgado 001; Maria-Amparo Vila; Derek T. Anderson; James M. Keller; Mihail Popescu (FUZZ-IEEE, 2011)

A common framework for information sharing in e-learning management systems. - Manuel P. Cuéllar; Miguel Delgado 001; Maria del Carmen Pegalajar Jiménez (Expert Syst. Appl., 2011)

Improving learning management through semantic web and social networks in e-learning environments. - Manuel P. Cuéllar; Miguel Delgado 001; Maria del Carmen Pegalajar Jiménez (Expert Syst. Appl., 2011)

Similarity measure for anomaly detection and comparing human behaviors. - Derek T. Anderson; María Ros; James M. Keller; Manuel P. Cuéllar; Mihail Popescu; Miguel Delgado 001; Maria-Amparo Vila (Int. J. Intell. Syst., 2012)

A Compact Optical Instrument with Artificial Neural Network for pH Determination. - Sonia Capel-Cuevas; Nuria López-Ruiz; Antonio Martínez-Olmos; Manuel P. Cuéllar; Maria del Carmen Pegalajar Jiménez; Alberto J. Palma; Ignacio de Orbe-Payá; Luis F. Capitán-Vallvey (Sensors, 2012)

Extending Semantic Web Tools for Improving Smart Spaces Interoperability and Usability. - Natalia Díaz Rodríguez; Johan Lilius; Manuel Pegalajar Cuéllar; Miguel Delgado Calvo-Flores (DCAI, 2013)

Rapid prototyping of semantic applications in smart spaces with a visual rule language. - Natalia Díaz Rodríguez; Johan Lilius; Manuel Pegalajar Cuéllar; Miguel Delgado Calvo-Flores (UbiComp (Adjunct Publication), 2013)

An approach to improve semantics in Smart Spaces using reactive fuzzy rules. - Natalia Díaz Rodríguez; Johan Lilius; Manuel P. Cuéllar; Miguel Delgado Calvo-Flores (IFSA/NAFIPS, 2013)

Understanding Movement and Interaction: An Ontology for Kinect-Based 3D Depth Sensors. - Natalia Díaz Rodríguez; Robin Wikström; Johan Lilius; Manuel Pegalajar Cuéllar; Miguel Delgado Calvo-Flores (UCAmI, 2013)

A survey on ontologies for human behavior recognition. - Natalia Díaz Rodríguez; Manuel P. Cuéllar; Johan Lilius; Miguel Delgado Calvo-Flores (ACM Comput. Surv., 2013)

Online recognition of human activities and adaptation to habit changes by means of learning automata and fuzzy temporal windows. - María Ros; Manuel P. Cuéllar; Miguel Delgado 001; Maria-Amparo Vila (Inf. Sci., 2013)

Human Activity Recognition Framework in Monitored Environments. - Olmo León; Manuel P. Cuéllar; Miguel Delgado 001; Yann-Aël Le Borgne; Gianluca Bontempi (ICPRAM, 2014)

An Approach for the Evaluation of Human Activities in Physical Therapy Scenarios. - Manuel P. Cuéllar; María Ros; María J. Martín-Bautista; Yann-Aël Le Borgne; Gianluca Bontempi (MONAMI, 2014)

Design and implementation of intelligent systems with LEGO Mindstorms for undergraduate computer engineers. - Manuel P. Cuéllar; Maria del Carmen Pegalajar (Comput. Appl. Eng. Educ., 2014)

A fuzzy ontology for semantic modelling and recognition of human behaviour. - Natalia Díaz Rodríguez; Manuel P. Cuéllar; Johan Lilius; Miguel Delgado Calvo-Flores (Knowl. Based Syst., 2014)

Handling Real-World Context Awareness, Uncertainty and Vagueness in Real-Time Human Activity Tracking and Recognition with a Fuzzy Ontology-Based Hybrid Method. - Natalia Díaz Rodríguez; Olmo León Cadahía; Manuel Pegalajar Cuéllar; Johan Lilius; Miguel Delgado Calvo-Flores (Sensors, 2014)

A novel approach for real-time learning and recognition of human activities. - Olmo León; Manuel P. Cuéllar; Miguel Delgado 001 (J. Ambient Intell. Smart Environ., 2016)

Experimental Evaluation of Straight Line Programs for Hydrological Modelling with Exogenous Variables. - Ramón Rueda Delgado; Luis Gonzaga Baca Ruiz; Patricia Jimeno-Sáez; Manuel Pegalajar Cuéllar; David Pulido-Velazquez; Maria del Carmen Pegalajar (HAIS, 2017)

Preliminary Evaluation of Symbolic Regression Methods for Energy Consumption Modelling. - Ramón Rueda Delgado; Manuel P. Cuéllar; Miguel Delgado 001; Maria del Carmen Pegalajar (ICPRAM, 2017)

A Comparison Between NARX Neural Networks and Symbolic Regression: An Application for Energy Consumption Forecasting. - Ramón Rueda Delgado; Luis G. Baca Ruíz; Manuel Pegalajar Cuéllar; Miguel Delgado Calvo-Flores; Maria del Carmen Pegalajar Jiménez (IPMU (3), 2018)

Energy consumption forecasting based on Elman neural networks with evolutive optimization. - Luis Gonzaga Baca Ruiz; Ramón Rueda Delgado; Manuel P. Cuéllar; Maria del Carmen Pegalajar (Expert Syst. Appl., 2018)

Straight line programs for energy consumption modelling. - Ramón Rueda Delgado; Manuel P. Cuéllar; Maria del Carmen Pegalajar; M. Delgado (Appl. Soft Comput., 2019)

Parallel memetic algorithm for training recurrent neural networks for the energy efficiency problem. - Luis G. Baca Ruíz; Manuel I. Capel; Manuel P. Cuéllar (Appl. Soft Comput., 2019)

An Ant Colony Optimization approach for symbolic regression using Straight Line Programs. Application to energy consumption modelling. - Ramón Rueda Delgado; Luis G. Baca Ruíz; Manuel P. Cuéllar; Maria del Carmen Pegalajar Jiménez (Int. J. Approx. Reason., 2020)

Automatic Label Creation Framework for FMCW Radar Images Using Camera Data. - Javier Mendez 001; Stephan Schoenfeldt; Xinyi Tang; Jakob Valtl; Manuel P. Cuéllar; Diego Pedro Morales (IEEE Access, 2021)

Gesture Recognition With Ultrasounds and Edge Computing. - Borja Saez; Javier Mendez 001; Miguel Molina; Encarnación Castillo; Manuel Pegalajar; Diego Pedro Morales (IEEE Access, 2021)

Analysis and enhanced prediction of the Spanish Electricity Network through Big Data and Machine Learning techniques. - Manuel Pegalajar Cuéllar; Luis G. Baca Ruíz; Manuel P. Cuéllar; Ramón Rueda Delgado (Int. J. Approx. Reason., 2021)

Analysis and enhanced prediction of the Spanish Electricity Network through Big Data and Machine Learning techniques. - Manuel Pegalajar Cuéllar; Luis G. Baca Ruíz; Manuel P. Cuéllar; Ramón Rueda Delgado (Int. J. Approx. Reason., 2021)

A Three-valued Logic Approach for Edge Detection Using Cellular Automata. - Manuel P. Cuéllar; Ramón Rueda Delgado; Luis Gonzaga Baca Ruiz; Maria del Carmen Pegalajar (J. Cell. Autom., 2021)

Camera-LiDAR Multi-Level Sensor Fusion for Target Detection at the Network Edge. - Javier Mendez 001; Miguel Molina; Noel Rodriguez; Manuel P. Cuéllar; Diego Pedro Morales (Sensors, 2021)

Air-Writing Character Recognition with Ultrasonic Transceivers. - Borja Saez-Mingorance; Javier Mendez-Gomez 001; Gianfranco Mauro; Encarnación Castillo Morales; Manuel Pegalajar Cuéllar; Diego P. Morales-Santos (Sensors, 2021)

Genetic algorithms with permutation-based representation for computing the distance of linear codes. - Manuel P. Cuéllar; José Gómez-Torrecillas; Francisco Javier Lobillo; Gabriel Navarro 001 (Swarm Evol. Comput., 2021)

Few-Shot User-Definable Radar-Based Hand Gesture Recognition at the Edge. - Gianfranco Mauro; Mateusz Chmurski; Lorenzo Servadei; Manuel Pegalajar Cuéllar; Diego P. Morales-Santos (IEEE Access, 2022)

Electric demand forecasting with neural networks and symbolic time series representations. - David Criado-Ramón; Luis G. Baca Ruíz; Manuel P. Cuéllar (Appl. Soft Comput., 2022)

A similarity measure for Straight Line Programs and its application to control diversity in Genetic Programming. - Ramón Rueda Delgado; Manuel P. Cuéllar; Luis G. Baca Ruíz; Maria del Carmen Pegalajar (Expert Syst. Appl., 2022)

Power-Efficient Implementation of Ternary Neural Networks in Edge Devices. - Miguel Molina; Javier Mendez 001; Diego Pedro Morales; Encarnación Castillo; Marisa López-Vallejo; Manuel Pegalajar (IEEE Internet Things J., 2022)

Edge Intelligence: Concepts, Architectures, Applications, and Future Directions. - Javier Mendez 001; Kay Bierzynski; Manuel P. Cuéllar; Diego Pedro Morales (ACM Trans. Embed. Comput. Syst., 2022)

Time Series Forecasting with Quantum Neural Networks. - Manuel P. Cuéllar; Maria del Carmen Pegalajar; Luis G. Baca Ruíz; Carlos Cano Gutierrez (IWANN (1), 2023)

Efficient Dimensionality Reduction Strategies for Quantum Reinforcement Learning. - Eva Andrés; Manuel P. Cuéllar; Gabriel Navarro 001 (IEEE Access, 2023)

AirLoop: A Simulation Framework for Testing of UAV Services. - Jessica Giovagnola; Juan B. Moro Megías; Miguel Molina Fernández; Manuel Pegalajar Cuéllar; Diego P. Morales-Santos (IEEE Access, 2023)

Few-Shot User-Adaptable Radar-Based Breath Signal Sensing. - Gianfranco Mauro; Maria De Carlos Diez; Julius Ott; Lorenzo Servadei; Manuel P. Cuéllar; Diego P. Morales-Santos (Sensors, 2023)

Fast parallel computation of reduced row echelon form to find the minimum distance of linear codes. - Manuel P. Cuéllar; Francisco Javier Lobillo; Gabriel Navarro 001 (Expert Syst. Appl., 2023)

Context-adaptable radar-based people counting via few-shot learning. - Gianfranco Mauro; Ignacio Martinez-Rodriguez; Julius Ott; Lorenzo Servadei; Robert Wille; Manuel P. Cuéllar; Diego P. Morales-Santos (Appl. Intell., 2023)

CUDA-bigPSF: An optimized version of bigPSF accelerated with graphics processing Unit. - David Criado-Ramón; Luis G. Baca Ruíz; Manuel P. Cuéllar (Expert Syst. Appl., 2023)

Time series quantum classifiers with amplitude embedding. - Manuel P. Cuéllar; Carlos Cano Gutierrez; Luis G. Baca Ruíz; Lorenzo Servadei (Quantum Mach. Intell., 2023)

Implementation of Classical Decision Trees in a Quantum Computing Paradigm. - Manuel P. Cuéllar; Luis Gonzaga Baca Ruiz; M. C. Pegalajar (HAIS (1), 2024)

On the fusion of soft-decision-trees and concept-based models. - David M. Rodríguez; Manuel P. Cuéllar; Diego Pedro Morales (Appl. Soft Comput., 2024)

Concept logic trees: enabling user interaction for transparent image classification and human-in-the-loop learning. - David M. Rodríguez; Manuel P. Cuéllar; Diego Pedro Morales (Appl. Intell., 2024)

Automatic evolutionary design of quantum rule-based systems and applications to quantum reinforcement learning. - Manuel P. Cuéllar; Maria del Carmen Pegalajar; C. Cano (Quantum Inf. Process., 2024)

End-to-End Ultrasonic Hand Gesture Recognition. - Elfi Fertl; Do Dinh Tan Nguyen; Martin Krueger; Georg Stettinger; Rubén Padial-Allué; Encarnación Castillo; Manuel P. Cuéllar (Sensors, 2024)

Exploring methods for the generation of visual counterfactuals in the latent space. - David Morales; Manuel P. Cuéllar; Diego Pedro Morales (Pattern Anal. Appl., 2024)

What we can do with one qubit in quantum machine learning: ten classical machine learning problems that can be solved with a single qubit. - Manuel P. Cuéllar (Quantum Mach. Intell., 2024)

Brain-Inspired Quantum Neural Architectures for Pattern Recognition: Integrating QSNN and QLSTM. - Eva Andrés; Manuel Pegalajar Cuéllar; Gabriel Navarro 001 (CoRR, 2025)