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Extraction of the essential features from massive bands is a key issue in hyperspectral images classification. Plenty of feature extraction techniques can be found in the literature but most of these methods rely on the linear/stationary assumptions. The aim of this paper is to propose an alternative methodology based on the ensemble empirical mode decomposition (EEMD) and utilize the versatile support...
Climate is a nonlinear system, and the BP neural network algorithm or the Support Vector Machine (SVM) algorithm which is superior in dealing with nonlinear problems is usually used in the climate forecast. Meanwhile, the climatic time series also include nonstationary feature, so this paper introduces a new method of signal processing-the Empirical Mode Decomposition (EMD) algorithm for making climatic...
Decision tree support vector machine (DTSVM), which combines SVM and decision tree using the concept of dichotomy, is proposed to solve the multi-class fault diagnosis tasks. Since the classification performance of DTSVM is closely related to its structure, genetic algorithm is introduced into the formation of decision tree, to cluster the multi-classes with maximum distance between the clustering...
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