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The Computational Intelligence Research group of UNINOVA (CA3) main mission is to actively participate in applied research, supported by projects, by defining new concepts, methods and algorithms capable of solving real-world problems
Data fusion
In general, we can say that "Data Fusion" is any process of aggregating data from multiple sources into a single composite with higher information quality. This is a recent topic of research within CA3 and at this stage we mainly concentrate on information fusion, which is a type of data fusion.

The goal of information fusion is to combine heterogeneous information to obtain a single composite of potential comparable alternative solutions that can be classified and ranked. The crux of information fusion, which is a type of data fusion, is three-folded: (i) data must be comparable and numerical, using some normalization process; (ii) imprecision in data must be taken in consideration; (iii) an appropriate aggregation function to combine values into a single score must be selected.

Recently, the application of computational intelligence concepts and techniques to perform data/information fusion is emerging as a versatile tool and our research work follows this direction.

CA3 Relevant papers in this topic are (for more papers and downloads see publication section):

  • R. A. Ribeiro, A. Falcão, A.Mora, J. M. Fonseca. FIF: A Fuzzy information fusion algorithm based on multi-criteria decision making, Knowledge-Based Systems journal (2013).
  • A. Mora, J. M. Fonseca, R. Ribeiro. Real-time Image Recovery Using Temporal Image Fusion. IEEE Proceedings of the International Conference on Fuzzy Systems, FUZZIEEE, India, 7-10 July (2013).