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- W2153162583 abstract "This paper attempts to characterize the medical time series by quantifying the ruggedness of the time series. The presence of two close data points on the time axis implies that these points are along the time axis. It creates the fuzzy similarity. Following the principle similar causes create effects, we expect that the magnitudes corresponding to those two data points should also be similar. However, if other features are considered along with the time information, then those two apparently data points might look different. The closeness creates the fuzziness, the one-to-many relationship creates the roughness, and together they form fuzzy-roughness. If the ruggedness is expressed as the fuzzy-roughness, then in some time series it is observed that the fuzzy-roughness of a part of the time series is to that of the whole time series. Experiments on ICU data sets show that the ruggedness measure using the fuzzy-rough set based fractal dimension is more robust than the Hurst exponent which is used frequently to measure the ruggedness of a fractal time series." @default.
- W2153162583 created "2016-06-24" @default.
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- W2153162583 date "2002-11-13" @default.
- W2153162583 modified "2023-09-25" @default.
- W2153162583 title "Measures of ruggedness using fuzzy-rough sets and fractals: applications in medical time series" @default.
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- W2153162583 doi "https://doi.org/10.1109/icsmc.2001.973498" @default.
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