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There are many outliers in traffic flow data for various reasons. It has a serious impact on the data analysis and use. There are three main ways to identify anomalies but they each have definite limitations, especially when identifying and correcting the first category and the second category of outlier at the same time. In order to solve this problem, this paper presents a new way to identify anomalies...
This paper proposes a kind of combination forecast model based on the wavelet analysis. First, the insurance income time series is decomposed under a multi-scale by using the Mallat algorithm. So the approximate (low frequency) component and the detail (high frequency) component under the corresponding scale are obtained. Then, the trend and cycle are distilled from the decomposition and modeled separately...
This paper first carries on the elaboration to the least squares support vector machine (LS-SVM) forecast model. Basing on the theory of wavelet frame and the condition of the SVM kernel function, a method that generates wavelet kernel function of the support vector machine is proposed. Then the Mexican Hat wavelet is been selected to construct LS-SVM kernel function and form LS-SVM model based on...
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