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In this paper, a fault diagnosis method based on support vector machine (SVM) is proposed for gas turbine bearing. Firstly, through analysis and processing of vibration signals, the singular value decomposition related EEMD technique is applied to extract feature vectors of the signals. The results are used as the input of SVM classifier model. Then, by using the SVM network intelligence, the turbine...
In this paper, a long-team immersion of concrete in dilute sulfuric acid is carried out. On the basis of the experimental data, a time serious prediction model of concrete corrosion in sulfuric based on support vector machine (SVM) is developed. The design steps and learning algorithm are also given. Comparing with the test result, this model has good predictive function, with the suitable reconstructed...
Support vector machine (SVM) is a popular method for classification in data mining. The canonical duality theory provides a unified analytic solution to a wide range of discrete and continuous problems in global optimization. This paper presents a canonical duality approach for solving support vector machine problem. It is shown that by the canonical duality, these nonconvex and integer optimization...
Complex wavelet structural similarity (CW-SSIM) index has been proposed as a promising image similarity measure that is robust to small geometric distortions such as translation, scaling and rotation of images, but how to make the best use of it in image classification problems has not been deeply investigated. In this paper, we propose a novel “feature-extraction free” image classification algorithm...
Web news articles play an important role in stock market. Sentiment classification of news articles can help the investors make investment decisions more efficiently. In this paper, we implemented an approach of Chinese new words detection by using N-gram model and applied the result for Chinese word segmentation and sentiment classification. Appraisal theory was introduced into sentiment analysis...
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