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In recent years, air quality has become a severe environmental problem in China. Since bad air quality brought significant influences on traffic and people's daily life, how to predict the future air quality precisely and subtly, has been an urgent and important problem. In this paper, a Spatio-Temporal Extreme Learning Machine (STELM) method is proposed for air quality prediction. STELM considers...
In view of the defects of safety monitoring and comprehensive audit in information network boundaries of State Grid Corporation of China(SGCC), a kind of security audit technology based on one-class support vector machine(OCSVM) is proposed for the security audit of user access behavior. Firstly, feature selection, syntax parsing of SQL statements and numerical processing of audit log are completed...
Accurate forecasting for "net load", i.e., the difference between the renewable generations and loads, are important for economical and secure dispatch of power systems. Of course, it is significant to ensure sufficient levels of ancillary service, in particular regulation service. Previously, wind power, photovoltaic generation (PV) and loads are forecasted separately. In contrast, in this...
This paper reports robustness comparison of clustering-based multi-label classification methods versus non-clustering counterparts for multi-concept associated image and video annotations. In the experimental setting of this paper, we adopted six popular multi-label classification algorithms, two different base classifiers for problem transformation based multi-label classifications, and three different...
Existing sparse representation with subspace learning is hampered by the intersection of subspaces of bases. With structured sparsity to enable the prior knowledge of signal statistics, this paper proposes a novel compressive video sampling by subspace learning to minimize the intersection of subspaces. As the measurement, the block coherence is optimized with the regularized learning to generate...
Face recognition has been widely studied due to its importance in various applications. However, the case that both training images and testing images are corrupted is not well solved. To address such a problem, this paper proposes a semisupervised learning algorithm for robust face recognition. In particular, we consider three items in the proposed formulation. First, a low-rank and sparse representation...
We study a classic problem in wireless data communications in which receivers generally rely on training pilots for equalization of multi-path dispersive channel distortions. Traditional equalizers often require a substantial number of pilot symbols for effective channel compensation. To conserve limited channel bandwidth, we investigate novel equalization algorithms that can make more efficient use...
Firstly, the importance of subjects design in virtual maintenance training system is emphasized, and then the main factors that affect the design for subjects in virtual maintenance training are analyzed. Secondly, the detailed design process of virtual maintenance training subjects is illustrated based on the analysis of training requirements. Finally, this process is applied in the design of a concrete...
Transformer fault diagnosis based on relevance vector machine (RVM) is proposed. The advantages of the RVM over the support vector machine (SVM) are probabilistic predictions, automatic estimations of parameters, and the possibility of choosing arbitrary kernel functions. Most importantly, RVM is capable of comparable classification accuracy to SVM, but with fewer relevance vectors (RVs) and higher...
With air attack as a main battle mode in modern warfare, Civil Air Defense (CAD) plays an increasingly important role in information warfare.In order to effectively implement the training of CAD operations and improve its command ability,a demo system of CAD simulation has been developed by means of 3D-visualization. This system realizes the simulation based on LAN and Assistant decision support of...
Test question duplicate checking by the computer program is the requirement of construction of test question library. To enhance the availability of test question duplicate checking, course knowledge tree and domain term table are introduced in the paper. Based on the domain term table, the domain terms of test question can be easily identified, therefore, the calculating of similarity deals with...
Support Vector Machine (SVM) is based on statistical learning theory which developed from the common machine learning. It is an effective tool to deal with limited samples. This paper proposes a model of the dissolved gas analysis (DGA) of transformer based on Multi-class SVM. Firstly, with the combination of SVM multi-class classification methods one-versus-rest (1-v-r) and one-versus-one (1-v-1),...
This paper addresses the questions of improving convergence performance for back propagation (BP) neural network. For traditional BP neural network algorithm, the learning rate selection is depended on experience and trial. In this paper, based on Taylor formula the function relationship between the total quadratic training error change and connection weights and biases changes is obtained, and combined...
Fuzzy neural network, which is based on fuzzy theory and BP neural network, plays an important role in practical. But the difficulty is how to construct its structure model. In this paper, according to the hypostasis of hidden layer, a fuzzy neural network model based on fuzzy clustering is brought forward, in which features of the samples are extracted and output information is synthetically considered...
Based on the data from the fatigue test of Epoxy Molding Compound (EMC), firstly with a focus on the application problem of the instability between fitting and prediction error of BP neural network (BPNN), the prediction model of fatigue life for EMC materials is established. In this approach, the network structure is improved with initiative way by reducing input from the perspective of nodes with...
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