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In response to the roller bearing fault of the engineering vehicle, the excellent characteristics of time-frequency of wavelet packet is used to decompose the fault signal. Then we extract the necessary of the fault signals. Finally, we carry out the recognition of fault types using multi-class support vector machine and dynamic clustering algorithm brought forward in the paper. It is such a algorithm...
In order to resolve decision classification problem in multiple agents system, this paper first introduces the architecture of multiple agents system. It then proposes a support vector machines based assessment approach, which has the ability to learn the rules form previous assessment results from domain experts. Finally, the experiment are conducted on the artificially dataset to illustrate how...
This paper focuses on an effective and efficient support vector machine classification training algorithm for large samples. This method is called 'SVC iterative learning algorithm based on sample selection (short for SVCI)'. Initially, a sample selection strategy based on fuzzy c-means clustering is performed to select partial samples as the first training set, so that common decomposition algorithms...
Support vector machines (SVMS) were originally designed for binary classifications. For multi-classifications, they are usually converted into binary ones, and up to date, several methods have been proposed to decompose and reconstruct multi-class classification problems. In this paper, we compare the performance of these algorithms. They are applied to eight UCI data sets and the ten-folder method...
Named entity recognition (NER) is low-level semantics technology. Since it is simple and efficient, it has been widely applied in many systems such as machine translation, information retrieval, information extraction, question answering and summarization. The goal of named entity recognition is to classify names into some particular categories from text, such as the names of people, places, and organizations...
Support vector machines (SVMs) are originally designed for binary classifications. As for multi-classifications, they are usually converted into binary ones, up to now, several methods have been proposed to decompose and reconstruct multi-class classification problems. In order to enhance the performance of one-against-all algorithm for multi-classification, in this paper, we modify the decision function...
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