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• W2069612148 abstract "This paper intends to propose a novel clustering method based on ant colony (AC) algorithm. A new approach called TT-transform based time frequency analysis is used in processing the non-stationary power signal disturbances. The time-time transform is the inverse Fourier transform of S-transform. The proposed model is demonstrated using feature vector from the domain of power signal analysis, yielding promising results. Visual localization, detection and classification of non-stationary power signals problem is carried out through TT-transform to generate time-frequency contours for extracting relevant features and certain pertinent feature vectors are applied to the Fuzzy C-means Algorithm with ant colony optimization for power signal classification. From simulation results, it is shown that the proposed algorithm has superior performance when compared to particle swarm algorithm." @default.
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• W2069612148 date "2009-01-01" @default.
• W2069612148 modified "2023-09-26" @default.
• W2069612148 title "TT-ACO based power signal classifier" @default.
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• W2069612148 doi "https://doi.org/10.1109/nabic.2009.5393787" @default.
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