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Data mining techniques, especially classification methods, are receiving increasing attention from researchers and practitioners in the domain of petroleum exploration and production (E&P) in China. To extensively investigate the effects of feature selection and learning algorithms on the hydrocarbon reservoir prediction performance, taking three real-world multiclass problems as examples, namely...
Selective ensemble is effective for improve the classification performance through taking full advantage of the diversity and supplement between base classifiers. A BPSO (binary particle swarm optimization) based selective SVM ensemble approach is proposed to ensure the diversity and supplement among base classifiers in the training phase and high performance in the selection phase. Firstly, bootstrap...
Wall rock alteration is one of the major mineralization characteristics of hydrothermal deposits. In order to effectively extract information in hyperspectral remote sensing prospecting, it is necessary to objectively filter the spectral characteristics of altered rock and the closely correlative spectral characteristics in the mineralization forecast. Rough sets do not need the datapsilas additional...
In the past several years, the alert correlation methods have been advocated to discover high-level attack scenarios by correlating the low-level alerts. The causal correlation method based on prerequisites and consequences has great advantages in the process of correlating alerts. But it must depend on complicated background knowledge base and has some limits in discovering new attacks. The cluster...
In this paper, a robust and effective face detection method with HTF-Boosting is proposed. Firstly, a new feature, called Haar texture feature, is proposed that has many merits compared with Haar-Like feature. Secondly, a new Boosting algorithm, called Haar Texture Feature Boosting (HTF-Boosting), is proposed to construct strong face/nonface classifiers. The HTF-Boosting algorithm trains strong classifiers...
A feature fusion algorithm with application to facial expression recognition is presented. Firstly, the brows, eyes and mouth areas are segmented from the facial expression images, and are computed with Higher-order Local Auto-Correlation (HLAC) method, and the Weighted Principal Component Analysis (WPCA) is used to reduce dimensions secondly, in which the weights values are obtained according to...
This paper concentrates on tone recognition of Chinese whispered speech. Without fundamental frequencies, four-tone classification for Chinese has been assumed extremely difficult. Former studies suppose that it is the amplitude of whispered speech can be utilized for tone recognition. However, the amplitude of speech can be changed on purpose, especially in whispers. Then assumption has been made...
Remote sensing images classification is one of important approaches for recognizing interesting ground object. It is because there are several problems for normal classification methods, for example more manual intervention influence effect of classification, neighborhood information couldn't be utilized adequately, there is bad robustness to environment and so on, that particle swarm classifying...
This paper presents a novel method for fingerprint image quality. Five features are extracted from the fingerprint image to analyze the quality and the feature vector is formed from the five features. Then SVM classifier, which can solve small-sample learning problems with good generalization, is trained to classify the fingerprint image. The fingerprint image is separated into one of the three classes,...
The electronic tongue is a new measuring instrument, consist of the pattern recognition and an array of taste sensors which is used to examine the characteristics of liquid. Now it has a widely application in drink recognition. This article classifies three kinds of grape wine by the sensor arrays, first we use the principal components analytic method (PCA) to optimize the primitive sampled data,...
An automated method that detects early cancerous specimens based on image analysis is described. After acquisition and noise reduction, the microscope images are segmented into individual cell nucleus, from which the feature vectors of nucleus are calculated. The dimensionality of the feature vectors is then reduced using a method combing F-Score and random forest algorithms. The types of the cell...
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