Publicaciones (50) Publicaciones de Julio Fernández Ceniceros

2023

  1. PSO-PARSIMONY: A method for finding parsimonious and accurate machine learning models with particle swarm optimization. Application for predicting force–displacement curves in T-stub steel connections

    Neurocomputing, Vol. 548

2021

  1. PSO-PARSIMONY: A New Methodology for Searching for Accurate and Parsimonious Models with Particle Swarm Optimization. Application for Predicting the Force-Displacement Curve in T-stub Steel Connections

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. PSO-PARSIMONY: a New Methodology for Searching for Accurate and Parsimonious Models with Particle Swarm Optimization. Application for Predicting the Force-Displacement Curve in T-stub Steel Connections

    Hybrid Artificial Intelligent Systems: 16th International Conference, HAIS 2021. Bilbao, Spain. September 22–24, 2021. Proceedings

2018

  1. A novel hybrid strip finishing process to improve mechanical properties and reduce energy consumption

    International Journal of Material Forming, pp. 1-17

  2. Stacking ensemble with parsimonious base models to improve generalization capability in the characterization of steel bolted components

    Applied Soft Computing Journal, Vol. 70, pp. 737-750

2017

  1. Implementing a technically and economically viable system for recording data inside concrete

    Construction and Building Materials, Vol. 157, pp. 860-872

  2. Improving hotel room demand forecasting with a hybrid GA-SVR methodology based on skewed data transformation, feature selection and parsimony tuning

    Logic Journal of the IGPL, Vol. 25, Núm. 6, pp. 877-889

2016

  1. Hotel Reservation Forecasting Using Flexible Soft Computing Techniques: A Case of Study in a Spanish Hotel

    International Journal of Information Technology and Decision Making, Vol. 15, Núm. 5, pp. 1211-1234

  2. Teaching/learning methodologies based on microprojects and internationalization to increase students’ motivation ontechnical subjects

    Advances in Higher Education (edUPV, Editorial Universitat Politècnica de València), pp. 191-208

2015

  1. A numerical-informational approach for characterising the ductile behaviour of the T-stub component. Part 1: Refined finite element model and test validation

    Engineering Structures, Vol. 82, pp. 236-248

  2. A numerical-informational approach for characterising the ductile behaviour of the T-stub component. Part 2: Parsimonious soft-computing-based metamodel

    Engineering Structures, Vol. 82, pp. 249-260

  3. GA-PARSIMONY: A GA-SVR approach with feature selection and parameter optimization to obtain parsimonious solutions for predicting temperature settings in a continuous annealing furnace

    Applied Soft Computing Journal, Vol. 35, pp. 13-28

  4. Generation of daily global solar irradiation with support vector machines for regression

    Energy Conversion and Management, Vol. 96, pp. 277-286

  5. Improving hotel room demand forecasting with a hybrid GA-SVR methodology based on skewed data transformation, feature selection and parsimony tuning

    Lecture Notes in Computer Science, Vol. 9121, pp. 632-643

  6. Innovative Modular Building Manufactured Using Structural Black Poplar Plywood Panels

    Project Management and Engineering

  7. Microproject-based teaching/learning methodology focused on emerging technologies and international entities cooperation

    1ST INTERNATIONAL CONFERENCE ON HIGHER EDUCATION ADVANCES (HEAD'15)

2014

  1. Analysis and optimization of meshing techniques for cfd simulations of rubber extrusion dies

    Proceedings from the 18th International Congress on Project Management and Engineering: (Alcañiz, July 2014)

  2. Hybrid modelling of multilayer perceptron ensembles for predicting the response of bolted lap joints

    Logic Journal of the IGPL, Vol. 23, Núm. 3, pp. 451-462

  3. Methodology based on genetic optimisation to develop overall parsimony models for predicting temperature settings on annealing furnace

    Ironmaking and Steelmaking, Vol. 41, Núm. 2, pp. 87-98

  4. Overall models based on ensemble methods for predicting continuous annealing furnace temperature settings

    Ironmaking and Steelmaking, Vol. 41, Núm. 1, pp. 51-60