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Time series analysis is a branch of the strong application of statistical probability. It has a wide range of applications in the field of industrial automation, hydrology, geology, meteorology and other natural domain. However, the application in the oil field development is not extensive. Currently the one-dimensional single variable time series analysis method is used to predict oil and water production...
In SonicIR, when a single short pulse of 20 or 40kHz sound wave passes through materials with mechanical discontinuities, e.g., cracks with faying surfaces, it will ordinarily cause heating of those surfaces. This study investigates the effect of support vector machines (SVM), which is a machine-learning method based on the principle of structural risk minimization, as a classifier tool to identify...
The Support Vector Machine method has a good learning and generalization ability. Unfortunately, there are no comprehensive theories to guide the parameter selection of the SVM, which largely limits its application. In order to get the optimal parameters automatically, researchers have tried a variety of methods. Using genetic algorithms to optimize parameters of an SVM Classifier has become one of...
We present a new framework of anomalous payload detection system. First of all, frequent sequential patterns (FSPs) are mined from raw traffic payloads. Setting different supports, we have several level of description of normal payload. We extract each FSP feature using n-gram technique. Thus we can have a deeper insight of data flow. By using advanced clustering method to fulfill the feature reduction,...
This paper reconstructs multivariate functions from scattered data by a new multiscale technique. The reconstruction uses support vector regression model by positive definite reproducing kernels in Hilbert spaces. But it adopts techniques from wavelet theory and shift-invariant spaces to construct a new class of kernels as multiscale superpositions of shifts and scales of a single compactly supported...
An accurate friction model is necessary for friction compensation in radar servo systems or industrial robots. In order to obtain an accurate friction model, a method of friction modelling is proposed, based on support vector regression machines (SVRM) and real genetic algorithms (RGA). Three optimization problem formulations are proposed to realize the automatic optimal parameter selection of SVMR...
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