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Multivariate time series (MTS) exist in many applications. Due to all kinds of interference factors, missing data in MTS is inevitable. Aiming at this problem, a filling method based on least squares support vector machine (LSSVM) is proposed. Firstly, for the series containing missing data, similar series are searched, and its results are viewed as the training set. Secondly, to make use of the correlation...
This essay presents an efficient intelligent over-voltage hierarchical recognition system for 110kV substation based on LSSVM optimized by gridding optimal algorithm. It is very indispensable to analyze and find the causes of over-voltage for ameliorating insulation coordination in power system. According to analyzing field over-voltage data from over-voltage on-line monitoring devices installed in...
Feature extraction is an essential preprocessing step in machine learning and data mining. Generally, supervised feature extraction algorithms with prior knowledge outperform unsupervised ones without prior knowledge. In particular, nearly all existing supervised feature extraction algorithms employ class labels or pairwise constraints as supervised information. In this paper, we propose to employ...
Power supply fluctuation can be potential threat to the correct operations of processors, in the form of voltage emergency that happens when supply voltage drops below a certain threshold. Noise sensors (with either analog or digital outputs) can be placed in the nonfunction area of processors to detect voltage emergencies by monitoring the runtime voltage fluctuations. Our work addresses two important...
In order to determine the 3D motion of a point target from a monocular moving camera, a locating method is proposed by taking advantage of the property that the positions of the target in a short time are relative to each other and the kernel trick of least squares support vector machine (LS-SVM). This method has better noise immunity due to its robust estimation property, and has high accuracy as...
An MQDF-CNN hybrid model is presented for offline handwritten Chinese character recognition. The main idea behind MQDF-CNN hybrid model is that the significant difference on features and classification mechanisms between MQDF and CNN can complement each other. Linear confidence accumulation and multiplication confidence criteria are used for fusion outputs of MQDF and CNN. Experiments have been conducted...
The paper presents nonlinear modeling study of belt conveyor system using the least square support vector machine (LS-SVM). Belt conveyor is a nonlinear, severe disturbance and time-varying system. So far, most of the existing models are based on mechanism laws, which are very useful for belt conveyor design. However, they are too complicated to be applied to control system design. To facilitate a...
Power system stability is an important problem for secure system operation. Transient stability is one of key problems of power system stability. In this paper, support vector machines (SVM), a novel type learning method and based on statistical learning theory, is applied to assess the transient stability of power system after faults occur on transmission lines. Reactive and active powers of all...
To investigate the neural activity corresponding to different cognitive states, it is of great importance to localize the cortical areas that are associated with task-related modulation. In this paper, we propose a novel discriminant pattern source localization (DPSL) method to analyze MEG data. Unlike most traditional source localization methods that aim to find “dominant” sources, DPSL is developed...
Based on traditional Mineralization information extraction technology, use of spectral angle mapping method (SAM) and support vector machine (SVM) method, alteration information extraction are used in Inner Mongolia, Ulan Chubb. First, preprocessing the original ASTER remote sensing image, and then study of the ore-related alteration of geological, in view of the different altered information uses...
The support vector machine (SVM) is an algorithm based on structure risk minimizing principle, having high generalization ability. In the course of multi-sensor information fusion of industrial control, sensor has bigger nonlinearity and fuzzy relation between coefficient and relevant parameter. A kind of model and algorithm of multiple sensor information fusion based on the support vector machine...
Thumbnail cropping helps improve thumbnail readability by cropping images before shrinking them. In this paper we propose a learning based method for automatic thumbnail cropping. To this end, we use a support vector machine to learn a discriminative model that simultaneously captures the saliency distribution and spatial priors. The model is then used to determine the best cropping rectangle. The...
Normalized difference vegetation index (NDVI) is a very important vegetation index, which has been widely applied in research regarding global environmental and climatic change. In this work, 16-Day L3 Global 1 km SIN Grid NDVI data sets in Heihe River Basin from MODIS vegetation index (VI) products (MOD13A2) during 2003-2005 are extracted and used for generating a one-year new NDVI data based on...
A visual pattern recognition method based on optimized parallel coordinates is proposed in this paper. We first introduce the traditional theory of parallel coordinates and indicate that parallel coordinates has a potential for classification tasks due to its projective transformation interpretation. Nevertheless, some optimization is needed. The main aim of optimization is to hide the valueless information...
In this paper, the performance of safety management in building construction in China is summarily analyzed. Considered the factors of the underlying causes of the construction safety accidents including staff, equipment, material, technique and circumstance, and combined with the latest study achievement of construction safety management at home and abroad, the underlying causes of poor safety management...
The electronic mail (e-mail) concept makes it possible to communicate with many people in an easy and cheap way. Though email brought us such huge convenience, it also caused us trouble of managing the large quantities of spam mails received everyday. Without appropriate counter-measures, the situation seems to be worsening and spare email will eventually undermine the usability of email. To efficiently...
The goal of a text classification system is to determine whether a given document belongs to which of the predefined categories. An optimal SVM algorithm for text classification via multiple optimal strategies is proposed in this paper. The experimental results indicate that the proposed optimal classification algorithm yields much better performance than other conventional algorithms
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