The main objective of the COST action IC0702 "Combining Soft Computing Techniques and Statistical Methods to Improve Data Analysis Solutions" was to strengthen the dialogue between the statistics and soft computing research communities in order to cross-pollinate both fields and generate mutual improvement activities.

Soft computing, as an engineering science, and statistics, as a branch of mathematics, emphasize different aspects of data analysis. Soft computing focuses on obtaining working solutions quickly, accepting approximations and unconventional approaches. Its strength lies in its flexibility to create models that suit the needs arising in applications (context of discovery, model generation). In addition, it emphasizes the need for intuitive and interpretable models, which are tolerant to imprecision and uncertainty.

Statistics is more rigorous and focuses on establishing objective conclusions based on experimental data by analysing the possible situations and their (relative) likelihood (context of justification, model validation). It emphasizes the need for mathematical methods and tools to assess solutions and guarantee performance.

Bringing the two fields closer together will enhance the robustness and generalisability of data analysis methods, while preserving the flexibility to solve real-world problems efficiently and intuitively

The lectures and tutorials in this summer course pointed out the potential that lies in joint solutions and the transfer of ideas from one field to the other. They were intended to stimulate young researchers to explore methods from that field - soft computing or statistics - they were not so familiar with yet in order to broaden their view and trigger new ideas for fruitful interdisciplinary research


In 2007 the ECSC began offering specialized courses focused on promoting the dissemination of new trends, developments and applications of the different areas of Soft Computing among international students from different backgrounds. Furthermore, with the idea of serving as a way to transfer knowledge to society, there were roundtables and conferences open to the public aimed at showing the application of these techniques to solve real-world problems. The teaching staff of these courses is made up of researchers of the Centre, Scientific Committee members and other international experts.

Second Summer Course: Intelligent Data Analysis

International Summer Course on Medical Imaging using Bio-inspired and Soft Computing

Summer Course 2009 of COST Action IC0702: Soft Computing and Statistics

The development of new reasoning and decision making tools that can deal with uncertainty and imprecision leads to considerable scientific and technical progress. This training school brought different approaches, research lines and applications together and permited the trainees to explore synergies between different computational and mathematical methods, to structure promising new ideas and research projects, to develop new research lines, to generate scientific and technical knowledge and to increase the multidisciplinary of European researchers. The training school plan balanced topics from basic research lines and real-world applications.

CRF was a philosophical tendency intensive course, to reflect on new ideas in modern science and technology. It was mainly intended for people interested in the evolution of scientific and technological ideas. The course took place from September, the 12th to October, the 14th, 2011, at the European Centre for Soft Computing (ECSC) premises in Mieres (Asturias), Spain.

The Director of the CRF was Dr. Rudolf Seising (ECSC).

CRF consisted of the following five parts which were relevant to both, Computational Intelligence and Soft Computing:

  1. Reflections on the History of Fuzzy Sets and Systems, by Dr. Rudolf Seising.
  2. Reflections on Fuzzy Logic versus Classical Logic, by Prof. Dr. Enric Trillas.
  3. Reflections on Fuzzy Control, by Dr. Luis Argüelles.
  4. Reflections on Neuro-fuzzy and Evolutive Systems, by Prof. Dr. Claudio Moraga.
  5. Reflections on Computing with Words and Perceptions, by Dr. Gracian Triviño.

Each of the five parts of the course corresponded with two lectures of 1.5 hours by the professor, plus several joint seminars of two hours each. An additional set of complementary lectures were also offered by selected researches. Every professor supervised the personal work of one or two students.

The second edition of the ECSC Summer Course titled "Intelligent Data Analysis", had a great success with students from different parts of the world (Finland, Egypt, Italy, Portugal, etc.) and many from the Spanish Universities.

Besides, given the relevancy for the industrial and bussiness areas that have the Intelligent Data Analysis, we counted with members of technology centers and companies, as CARTIF Foundation, UNIOVA and LEIA Foundation.

Course Reflecting on Fuzziness - PHILOSOPHY, SCIENCE, TECHNOLOGY 

Spring School 2009 of COST Action IC0702: Reasoning and Decision Making under Uncertainty and Imprecision

First Summer Course: Future Directions in Soft Computing

The ECSC coordinated the 7FP Marie Curie Initial Training Network "Medical Imaging using Bio-inspired and Soft Computing" ( . This network aimed to create a multidisciplinary training programme where 16 enrolled early-stage researchers (ESRs) were exposed to a wide variety of Bio-Inspired (BC) and Soft Computing (SC) techniques, and to the challenge of applying them in the development of flexible application-oriented solutions to current Medical Imaging (MI) problems.

The MIBISOC partnership consisted of world-wide recognized researchers from 8 scientific institutions (ECSC, Ghent University, Université Libre de Bruxelles, University of Nottingham, Università degli Studi di Parma, University of Granada, Henesis, and Universitätsklinikum Freiburg), and 4 high quality technical partners (General Electrics Healthcare, CNRS, Hospital Central de Asturias, and Treelogic).

Within this training programme a first technical course was organized in July 2011. It was focused on SC and BC-based intelligent system design to solve real-world MI problems. A detailed summary of real-world applications was taught by outstanding experts, including topics such as image reconstruction in MI modalities, filtering and processing of medical images, segmentation and feature extraction in MI, range and multimodal image registration.

Soft Computing is a discipline that deals with the design of hybrid intelligent systems which, in contrast to classical hard computing techniques, are tolerant to imprecision, uncertainty, partial truth, and approximation. Thus tractable, robust, and low cost solutions to real-world problems are achieved. The main constituents of Soft Computing are fuzzy logic, neural networks, evolutionary computation, and probabilistic reasoning.

Since the term Soft Computing was coined at the beginning of the 90s, this area has experienced a rapid development of its fundamentals as well as its applications. The summer course reviewed the fundamentals of this discipline, described many real-world applications, and, in particular, treated new trends and future directions of the field. Participants gained insight into the potential of soft computing techniques and the state of the art in the area. To achieve this, the lecturers were selected from the leaders of the different branches of Soft Computing.

The summer course was supported by the "Future Directions in Fuzzy Sets and Systems" Task Force, Fuzzy Systems Technical Committee, IEEE Computational Intelligence Society, several members of which participate in the course.