• A Review of Classification Problems and Algorithms in Renewable Energy Applications 

      Pérez-Ortiz, María; Jiménez-Fernández, Silvia; Gutiérrez, Pedro A.; Alexandre, Enrique; Salcedo Sanz, S.; Hervás-Martínez, César (MDPI, 2016)
      Classification problems and their corresponding solving approaches constitute one of the fields of machine learning. The application of classification schemes in Renewable Energy (RE) has gained significant attention in ...
    • A Taxonomy of Information Attributes for Test Case Prioritisation: Applicability, Machine Learning 

      Ramírez, Aurora; Feldt, Robert; Romero, José Raúl (Association for Computing Machinery, 2023)
      Most software companies have extensive test suites and re-run parts of them continuously to ensure recent changes have no adverse effects. Since test suites are costly to execute, industry needs methods for test case ...
    • A weed monitoring system using UAV-imagery and the Hough transform 

      Pérez-Ortiz, María; Peña, J.M.; Gutiérrez, P.A.; Torres-Sánchez, J.; Hervás-Martínez, César; López-Granados, Francisca (2015)
      Usually, crops require the use of herbicides as a useful manner of controlling the quality and quantity of crop production. Although there are weed-free areas, the most common approach is to broadcast herbicides entirely ...
    • Artificial intelligence to automate the systematic review of scientific literature 

      De la Torre, José; Ramírez, Aurora; Romero, José Raúl (Springer, 2023)
      Artificial intelligence (AI) has acquired notorious relevance in modern computing as it effectively solves complex tasks traditionally done by humans. AI provides methods to represent and infer knowledge, efficiently ...
    • GEML: A grammar-based evolutionary machine learning approach for design-pattern detection 

      Barbudo Lunar, Rafael; Ramírez, Aurora; Servant, Francisco; Romero, José Raúl (Elsevier, 2021)
      Design patterns (DPs) are recognised as a good practice in software development. However, the lack of appropriate documentation often hampers traceability, and their benefits are blurred among thousands of lines of code. ...