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A new efficient technique for the classification of signals, in the form of earthquake-induced ground-acceleration time histories, according to the damage that they cause in buildings, is presented for the first time. A training set of real seismic accelerograms with well-known damage effects is utilised and fuzzy representations of prototype signals are extracted. These prototypes are selected with respect to the architectural and structural damage caused by the seismic-acceleration time histories. The classification of the unknown accelerograms takes place through a fuzzy comparison with the prototypes and each is classified to the most similar prototype. Real, seismic time-acceleration records were used for testing the algorithm and the high percentage of the correctly recognised signals prove the effectiveness of the algorithm. Correct classification rates of up to 84% are achieved.