The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Feature selection algorithm has a great influence on the accuracy of text categorization. The traditional information gain (IG) feature selection algorithm usually selects the features that rarely appear in the specified categories, but frequently appear in other categories. To overcome this drawback, on the basis of in-depth analysis of the related algorithms, an improved IG feature selection method...
Predicting soon-to-fail (STF) disks is fundamental to keeping disk data safe and enforcing quality of service. Most current proactive prediction approaches achieve high prediction rate at the cost of high false alarm rate, labeling healthy disks as STF, because of the imbalanced fraction of failed disks in the training dataset and the characteristics of the machine learning (ML) techniques used. Given...
Effective image parsing needs a representation that is both selective (to inter-class variations) and invariant (to intra-class variations). CodeBook from bag-of-visual-words representation addresses the invariance, and part-based models can potentially address the selectivity. However, existing part-based approaches either require expensive manual object-level labeling or make strong assumptions...
Using history climate data and two representative climate change scenarios, we predicted the potential distribution of bamboo in China from 1961 to 2099 based on specie distribution models. Through evaluating the impact of presence-only, true-absence and pseudo-absence data on SVM models accuracy on the potential distribution of bamboo during 1981–2000, we found that the two-class SVM using presence...
Discrete wavelet transform has both good qualities in time domain and frequency domain which is an ideal tool in analyzing unsteady signals. Discrete cosine transform is one of the approaches used in image compressing which is also used to extract features. This paper proposes a combined feature extraction method which is based on DWT and DCT for face recognition. First the original face image is...
The problem of end effects in Hilbert-Huang transform is produced in the Empirical Mode Decomposition (EMD), which has a badly effect on Hilbert-Huang transform. In order to overcome this problem, multi-objective Genetic Algorithm (GA) for solving the parameters selection of RBF Neural Network (RBF_NN) (GRHHT) is presented in this paper. Then the RBF_NN is used to predict the signal before EMD. The...
The end effects of Hilbert-Huang transform are produced in the Empirical Mode Decomposition(EMD) and the Hilbert transform for Intrinsic Mode Functions(IMF), which have a badly effect on Hilbert-Huang transform. In order to overcome this problem, the multi-objective allocation Genetic Algorithm (GA) to solve the kernel parameters selection of Least Squares Support Vector Machine (LSSVM)(GLHHT) is...
Intelligence is the core function of cognitive radio (CR). Intelligence is achieved by learning engine through knowledge acquisition. In this paper, a kind of learning engine is designed based on support vector machine (SVM). The proposed approach is demonstrated by data come from 802.11a protocol platform that the classification and regression results of SVM are very promising which ensure the effectiveness...
Rough set (RS) and support vector machine(SVM) have gradually been becoming hot spots in the territory of artificial intelligence, machine learning and data mining research. In this paper, RS and SVM theories have been discussed, a new hybrid RS-SVM model was proposed based on the attribute reduction of RS and the classification principles of SVM, which has been analyzed its possibility of application...
Abstract. Content-based audio classification and segmentation is a basis for further audio/video analysis. In this paper, we present our work on audio segmentation and classification which employs support vector machines (SVMs). Five audio classes are considered in this paper: silence, music, background sound, pure speech, and non- pure speech which includes speech over music and speech over noise...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.