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SOCO - Soft Computing

Total activity: 879
Research group
Type of group
UPC research group
C. Jordi Girona, 1-3, Edifici Omega Open in new window
08034 Barcelona
https://soco.upc.edu/en Open in new window
The term "soft computing" was coined in the nineties, and it describes the combined use of a variety of computational approaches that have been developed over the last few decades, which include but are not limited to fuzzy systems, neural networks and evolutionary algorithms.

Despite their obvious differences, a common trait of these fields is the abandonment of binary logic, static analytical models, rigid classifications and deterministic searches. In an ideal problem description, the systems that require modelling and/or control would be defined completely and precisely. In this case, formal reasoning systems can be used to associate Boolean values to state descriptions or physical systems' behaviour. Nevertheless, when tackling real-world problems, it is not unusual to find them incompletely or badly defined, which makes it difficult to model them and requires large search spaces. As a result, precise models, should they exist, might turn out to be impractical and/or costly. Usually, the relevant information that is available is presented either as empirical, a priori knowledge or as input-output instance descriptions of the systems' behaviour. This makes the use of approximate reasoning systems necessary, as they can flexibly cope with such far-from-perfect information.

The main goal of the SOCO group is to make progress in the state-of-the-art development of soft-computing methodologies, as well as to research their possible hybridisation in order to improve their robustness and efficacy. The SOCO group is currently working on the following research lines:

* Feature selection and dimensionality reduction

* Fuzzy systems (Fuzzy Inductive Reasoning, FIR)

* Artificial neural networks (feed-forward, recurrent, heterogeneous)

* Unsupervised probabilistic models

* Genetic algorithms and evolutionary strategies

* Pattern recognition and computer vision

* Hybrid soft-computing methods, including the following:

- Neural networks and support vector machines

- Fuzzy Inductive Reasoning and simulated annealing

- Fuzzy Inductive Reasoning and genetic algorithms

- Frequency selection for neural networks

- Cooperation of local experts for inductive reasoning

- Incremental construction of hybrid recurrent neural networks

The application of these methodologies to real-world problems is also one of the group's goals. The group has carried out research in the following areas of application:

* Medical (human central nervous system, cancer prediction, diagnosis, cognitive neuroscience, etc.)

* Biological (growth of white shrimp)

* Ecological (analysis of pollutant concentration in urban areas and ecological status modelling of streams)
Algorismes genètics i estratègies evolutives, Deep learning, Models probabilístics, Màquines de suport vectorial, Reducció de la dimensionalitat, Selecció de variables, Sistemes difusos, Soft Computing, Xarxes neurals
Fill in details (researchers incharge only)
  • Acosta Sarmiento, Jesus Antonio
    (until 2006-12-31)
  • Barrio Moliner, Ignacio
    (until 2008-02-16)
  • Castro Espinoza, Felix Agustin
    (until 2009-06-12)
  • Olier Caparroso, Ivan Alberto
    (until 2008-10-01)
  • Orozco Luquero, Jorge
    (until 2005-12-12)
  • Tosi, Alessandra
    (until 2015-03-10)

Scientific and technological production

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