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Identification and classification of fault signal in power systems is an important task. For the pattern recognition of disturbance signal, this paper presents five benchmarks of disturbance signal by MATLAB; Then, feature vectors of the disturbance signal which are extracted by the wavelet packet transforms; The vectors can be recognize by SVM multi — classifier. Numerical results show this approach...
Virtual human motion capture data has been widely applied in virtual reality, computer animation, etc. It is important to segment the motion data into small clips automatically in order to reuse these data. In this paper, a new method of motion capture data segmentation is proposed based on kernel dynamic texture. First we model the motion capture data using kernel dynamic texture, and then on the...
The quality of peanut kernels is referred to the every aspect of the profit of supply and marketing. A BP neural network model of quality grade testing and identification is built which is based on 52 appearance features such as the form, texture, and color and so on with technology of computer image processing. The testing aiming at 1400 grains is made separately in unsound kernel, mildewing, impurity,...
This study develops a novel methodology hybridizing genetic algorithms (GAs) and support vector regression (SVR) and implements this model in a problem forecasting hourly cooling load. The aim of this study is to examine the feasibility of SVR in building cooling load forecasting by comparing it with back-propagation neural networks (BPNN) and the autoregressive integrated moving average (ARIMA) model...
In order to solve the problem of non-linear in mixed gas infrared spectra analysis, the data fusion method based on support vector machine is used. Data fusion is a new information processing method, and it may use superfluous and complementary information to improve the performance of output, and the data fusion model is established. The non-linear processing function of support vector machine is...
In order to counterbalance the unfairness to rare class on using Support Vector Machine to credit assess for imbalanced dataset from commercial banks, an adjustment Method of the separating hyperplane is proposed in the paper. Based on Fisher discrimination, the projected class mean and variance are got by projecting two classes samples onto the normal vector of the separating hyperplane, then adjust...
In order to solve the manufacturing time series forecasting problem, a grey support vector machines (GSVM) with differential evolution algorithms is proposed. GM (1, N) model of grey system is used to add a grey layer before neural input layer and white layer after support vector machine layer. Differential evolution (DE) algorithm is used to determine free parameters of support vector machines. Evaluation...
The environment is the key to the success of real estate investment. Therefore, it is very important for the investment environment evaluation of real estate. Firstly, the basic theory of support vector machine for regression (SVR) was introduced, and then a SVM to evaluate the investment environment of real estate was built. Through simulating and comparing with the method of BP neural network, the...
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