Abstract
Functional brain imaging is a source of spatio-temporal data mining problems. A new framework hybridizing multi-objective and multi-modal optimization is proposed to formalize these data mining problems, and addressed through Evolutionary Computation (EC).
The merits of EC for spatio-temporal data mining are demonstrated as the approach facilitates the modelling of the experts’ requirements, and flexibly accommodates their changing goals.
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Krmicek, V., Sebag, M. (2006). Functional Brain Imaging with Multi-objective Multi-modal Evolutionary Optimization. In: Runarsson, T.P., Beyer, HG., Burke, E., Merelo-Guervós, J.J., Whitley, L.D., Yao, X. (eds) Parallel Problem Solving from Nature - PPSN IX. PPSN 2006. Lecture Notes in Computer Science, vol 4193. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11844297_39
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DOI: https://doi.org/10.1007/11844297_39
Publisher Name: Springer, Berlin, Heidelberg
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