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Research group “Metrology and Models”

Participating University Departments:

• Computer Sciences and Artificial Intelligence (Ciencias de la Computación e Inteligencia Artificial, Departamento de Informática)
• Computer Languages and Systems (Lenguajes y Sistemas Informáticos, Departamento de Informática)
• Statistics and Operational Research (Estadística e Investigación Operativa, Departamento de Estadística e Investigación Operativa y Didáctica de las Matemáticas)

Research Lines

• Knowledge modeling from low quality data
• Fusion of sensor information and computer vision in dimensional metrology
• Soft Computing based techniques for improving the energetic efficiency in buildings

Members

• Luciano Sánchez Ramos
• Inés Couso Blanco
• José Otero Rodríguez
• Enrique A. De la Cal Marín
• M. del Rosario Suárez Fernández
• José Ramón Villar Flecha
• Ana María Palacios Jimémez
• Adolfo Otero Rodríguez
• Luis Junco Navascués

Activity of the group in the last five years

The research group “Metrology and Models’ was founded in 2002. Since then, the group has dedicated itself to the theoretical research of intelligent systems for extracting knowledge from data, and to the practical applications of these techniques to practical problems of modeling and industrial metrology. The fundamental research of the group is oriented to the robust design of classifiers and regression models from imprecisely perceived data, and to statistical techniques for analyzing the results of these models. The research of this group has given rise to a number of industrial applications and patents. This group has also spinned off the technological startup IDALIA S.L., which transfer the academic research results into industrial products.

Quality indicators of the scientific production

As quality indicators of the scientific production of the group we mention the following recent publications in JCR-indexed journals:

• Learning of linguistically understandable intelligent systems
  • J. Otero, L. Sánchez. Induction of descriptive fuzzy classifiers with the Logitboost algorithm. Soft Computing 10(9) 825-835 (2006)
  • R. Alcalá, J. Alcala-Fdez, F. Herrera, J. Otero. Genetic Learning of Accurate and Compact Fuzzy Rule Based Systems Based on the 2-Tuples Linguistic Representation. International Journal of Approximate Reasoning 44(1) 45-64. (2007)
  • L. Sánchez, J. Otero. Boosting fuzzy rules in classification problems under single-winner inference. International Journal of Intelligent Systems 22(9) 1021-1035. (2007)
  • J.R. Villar, L. Sánchez. Obtaining transparent models of chaotic systems with multiobjective simulated annealing algorithms. Information Sciences 178(4) 952-970 (2008)
• Model design from low quality data
  • L. Sánchez, I. Couso. Advocating the use of Imprecisely Observed Data in Genetic Fuzzy Systems. IEEE Transactions on Fuzzy Systems 15 (4), 551-562 (2007)
  • J. Otero, L. Sánchez, J. Alcala-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), 751-764 (2008)
  • Sánchez, L., Suárez, M. R., Villar, J. R., Couso, I. Mutual Information-based Feature Selection and Fuzzy Discretization of Vague Data. International Journal of Approximate Reasoning 49 (3), 607-622 (2008)
  • Villar, J. R., Otero, A., Otero, J., Sánchez, L. Taximeter verification using Imprecise Data from GPS and Multiobjective Algorithms. Engineering Applications of Applied Intelligence 22 (2), 250-260 (2009)
  • Sánchez, L., Otero, J., Couso, I. Obtaining Linguistic Fuzzy Rule-based Regression Models from Imprecise Data with Multiobjective Genetic Algorithms. Soft Computing 13 (3), 307-318. (2009)
  • Villar, J. R., Otero, A., Otero, J., Sánchez, L. Taximeter verification with GPS and soft computing techniques. Soft Computing 14 (4) 405-418. (2009)
  • Villar, J. R., de la Cal, E. A., Sedano, J. A fuzzy logic based efficient energy saving approach for domestic heating systems. Integrated Computer-Aided Engineering 16 (2), 151-163. (2009)
  • Sánchez, L., Couso, I., Casillas, J. Genetic Learning of Fuzzy Rules based on Low Quality Data. Fuzzy Sets and Systems 160(17) 2524-2552. (2009)
  • Palacios, A., Sánchez, L., Couso, I. Extending a simple cooperative-competitive learning fuzzy classifier to low quality datasets. Evolutionary Intelligence 2 (1-2), 73-84. (2010)
  • Palacios, A., Sánchez, L., Couso, I. Diagnosis of dyslexia with low quality data with genetic fuzzy systems. International Journal on Approximate Reasoning 51, 993-1009. (2010)
  • Sánchez, L. Couso, I. Obtaining fuzzy rules from interval-censored data with genetic algorithms and a random sets-based semantic of the linguistic labels. Soft Computing. Doi 10.1007/s00500-010-0627-6. (2010)
  • Sedano, J., Curiel, E., Corchado, E., de la Cal, E. A., Villar, J. R. A soft computing method for detecting lifetime building thermal insularion failures. Integrated Computer-Aided Engineering 17 (2), 103-115. (2010)
  • Palacios, A. Sánchez, L., Couso, I. Future performance modelling in athletism with low quality data-based GFSs. Journal of Multivalued Logic and Soft Computing (Admitido). (2011)
• Statistical learning of algorithms
  • I. Couso, L. Sánchez. Higher order models for fuzzy random variables. Fuzzy Sets and Systems 159 (3), 237-258 (2008)
  • I. Couso, L. Sánchez, Mark-recapture techniques in statistical tests for imprecise data. International Journal of Approximate Reasoning. doi 10.1016/j.ijar.2010.07.009 (2010)

Public grants

In the list 5 years, the research activities have been funded by two grants:

• 2005-2008: KEEL II: Extracción de conocimiento basada en prototipos difusos evolutivos. Modelos basados en datos imprecisos. Análisis de las metodologías de comparación de algoritmos. Análisis de experimentos. (MICINN cod. TIN2005-08386-C05-05)
• 2008-2011: KEEL-CTNC: Modelos de Aprendizaje Evolutivo basados en Datos de Baja Calidad. (MICINN cod. TIN2008-06681-C06-04)

Research contracts

Most relevant technologic transference activities in the last three years:

• 2007: Diseño y desarrollo de un taxímetro patrón usando tecnología GPS. (ITVASA)
• 2008-2009: FESAC. Fuzzy Energy Saving and Control (González Soriano, S.A.)
• 2009-2010: Desarrollo de sistemas de análisis de información con técnicas de inteligencia artificial (ECSC).
• 2010-2012: CONSOCO: Conformado por medio de Soft Computing (Instituto Tecnológico de Castilla y León)
• 2010-2013: ORIGIN: ORganizaciones Inteligentes Globales INnovadoras (TREELOGIC, S.L)

Patents

Patents covering the technology developed in the group:

• Inventors: Otero, J., Sanchez, L., Otero, A. Taxímetro patrón usando tecnología GPS. Ref. ES-2335841-A1 . Assignee: ITVASA.
• Inventors: J. Sedano, J. R. Villar, E. de la Cal, V. M. González. Procedimiento y dispositivo difuso multiagente para la racionalización del consumo de calefacción eléctrica de uso doméstico. Ref. P200931012. Assignee: González Soriano, S. A.
• Inventors: J. Cueli, L. Sánchez. Sistema de monitorización de la resistencia de protección de un transformador trifásico. Ref. P201030243. Assignee: Electromateriales KLK, S. A.