Publicaciones en las que colabora con Rubén Urraca Valle (24)

2017

  1. Assessment of microproject-based teaching/learning (MicroPBL) experience in industrial engineering degrees

    Proceedings of the HEAd’17. 3rd International Conference on Higher Education Advances (Editorial Universitat Politècnica de València), pp. 268-276

  2. Estimation methods for global solar radiation: Case study evaluation of five different approaches in central Spain

    Renewable and Sustainable Energy Reviews, Vol. 77, pp. 1098-1113

  3. 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

  4. Metodología basada en máquinas DO-IT-YOURSELF y Microproyectos Internacionales para la docencia en los Grados de ingeniería

    Metodología basada en máquinas DO-IT-YOURSELF y Microproyectos Internacionales para la docencia en los Grados de ingeniería

  5. Practical methodology for validating constitutive models for the simulation of rubber compounds in extrusion processes

    International Journal of Advanced Manufacturing Technology, Vol. 90, Núm. 5-8, pp. 2377-2387

  6. Quality control of global solar radiation data with satellite-based products

    Solar Energy, Vol. 158, pp. 49-62

2016

  1. Estimation of total soluble solids in grape berries using a hand-held NIR spectrometer under field conditions

    Journal of the Science of Food and Agriculture, Vol. 96, Núm. 9, pp. 3007-3016

2015

  1. DESARROLLO DE “MICRO-PROYECTOS BASADOS EN TECNOLOGÍAS EMERGENTES” MEDIANTE LA COLABORACIÓN CON ENTIDADES INTERNACIONALES DENTRO DE LOS NUEVOS GRADOS DE INGENIERÍA. 3º ETAPA.

    DESARROLLO DE “MICRO-PROYECTOS BASADOS EN TECNOLOGÍAS EMERGENTES” MEDIANTE LA COLABORACIÓN CON ENTIDADES INTERNACIONALES DENTRO DE LOS NUEVOS GRADOS DE INGENIERÍA. 3º ETAPA.

  2. 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

  3. On-line Soft Sensor Based on Regression Models and Feature Selection Techniques for Predicting Rubber Properties in Mixture Processes

    Project Management and Engineering, pp. 235-245

  4. On-line soft sensor based on regression models and feature selection techniques for predicting rubber properties in mixture processes

    Project Management and Engineering: Selected Papers from the 17th International AEIPRO Congress held in Logroño, Spain, in 2013

2014

  1. Soft computing metamodels for the failure prediction of T-stub bolted connections

    Advances in Intelligent Systems and Computing, pp. 41-51