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With the advent of high-efficiency technology of digital image processing and pattern classification, the research on classification for tool marks is catching forensic scientist's eyes. It is crucial for classification to extract and select the features from tool marks. In the practical situation, the geometrical shapes and the textures of tool marks are complex, irregular and stochastic. It is difficult...
Accurate identification and classification of network traffic according to application type is an important element of many network management tasks. In this paper, a P2P network traffic classification method using SVM classifier is proposed. By this method, the P2P network traffic can been classified according to application types with statistical characteristics of network traffic. This paper mainly...
Data mining is a new filed in data processing research. Support vector machine (SVM) is one of the new methods using in data mining, which has gained great applicable success. However, there are stiff plenty of limitations in SVM. For example, SVM won't work if its training set contains fuzzy information. In order to solve the problem presented above, this article discusses the constraining programming...
When the training subset of a support vector machine contains fuzzy information, the support vector machine won't work. A method for calculating fuzzy linear separable support vector classifier is discussed. With the given confidence level, convert the fuzzy classification problem into finding the fuzzy chance constrained programming, and establish a solution finding theory with fuzzy chance constrained...
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