Grupo ISIS

Computational Intelligence

Description

The area of advanced computing has as main objective theoretical study and practical implementation of several techniques of computational intelligence to engineering problems. Over the past years, the group has contributed significantly to the improvement of paradigms of advanced computing such as are neural networks (NN) and genetic algorithms (GA) through numerous scientific works and doctoral theses, as well as its application of several engineering problems.

 

Among the most prominent works in this area include the implementation of the RNA to the management of electrical power and water systems, forecasting of temporal series and robotic.

At present, the group is working in the application of these techniques to autonomous mobile systems, the modeling of dynamical systems and to the realization of measurements of very high precision of power energy under non-sinusoidal conditions.

Members

• Joya Caparrós, Gonzalo
• García Lagos, Francisco
• Atencia Ruiz, Miguel
• Sandoval Hernández, Francisco
• de Harazoza Rodríguez, Héctor

Publications

• Searching the shortest pair of edge-disjoint paths in a Communication Network. A Fuzzy approach
• Feature Selection of EEG Oscillatory Activity Related to Motor Imagery Using a Hierarchical Genetic Algorithm
• A wearable fall detection system using deep learning
• Advances in Computational Intelligence Part I: 15th International Work-Conference on Artificial Neural Networks, IWANN 2019
• Advances in Computational Intelligence Part II: 15th International Work-Conference on Artificial Neural Networks, IWANN 2019

Projects

• DIATAX: Integración de nuevas tecnologías para el diagnóstico temprano de las Ataxias Hereditarias
• AVANCES EN EL DISEÑO Y ADAPTACION DE ALGORITMOS DE APRENDIZAJE PROFUNDO PARA SU APLICACION A PROBLEMAS EN LAS AREAS DE BIOMEDICINA Y CONTAMINACION ATMOSFERICA
• DESARROLLO DE TÉCNICAS AVANZADAS Y SOSTENIBLES PARA LA REHABILITACIÓN TECNOLÓGICA, RESILIENTE Y EFICIENTE DE PAVIMENTOS DE CARRETERAS (REPARA 2.0)
• Diseño de estrategias adaptativas en sensores inteligentes y aplicacion a la predicción de contaminantes atmosféricos en entornos locales
• Creación de un grupo interuniversitario para la investigación y la docencia en técnicas bioinspiradas y de inteligencia computacional. Aplicación al estudio de epidemias y enfermedades raras de especial incidencia en Cuba y al control de sistemas.