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27 de feb. de 2024 · In this work, we study this problem from a new direction and develop a multi-attribute source estimator (MASE) and its extension Fuzzy-MASE. The proposed framework allows us to transform source localization into a multi-attribute decision-making (MADM) problem, ensuring better flexibility and extensibility.
In statistics, the mean absolute scaled error (MASE) is a measure of the accuracy of forecasts. It is the mean absolute error of the forecast values, divided by the mean absolute error of the in-sample one-step naive forecast.
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22 de sept. de 2014 · MASE provides a measure of how accurate forecasts are for a given series and the $Q$ scaling is intended to allow comparisons between series of different scales. Suppose $y_t$ is standard Gaussian white noise $N(0,1)$. Then the data has variance 1, and the optimal forecast is $\hat{y}_{T+k|T}=0$ with forecast variance $v_{T+k|T} = 1$.
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