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Exchange rate time series is often characterized as chaotic in nature. The prediction using conventional statistical techniques and neural network with back propagation algorithm, which is most widely applied, do not give reliable prediction results. Exchange-rate time series is also a dynamic non-linear system, whose characteristics cannot be reflected by the static neutral network. The Nonlinear...
Support vector machine (SVM) is discussed to use for recognizing cucumber leaf diseases in this paper. Considering that it is a small number of samples, a new experimental program has been proposed which takes each spot of leaves as a sample instead of taking each leaf as a sample. In the experiments Radial Basis Function (RBF), polynomial and Sigmoid kernel function were also used to carry out comparative...
A soft sensor was developed to estimate the concentrate grade and recovery rate of a flotation circuit. The algorithm uses kernel principal component analysis (KPCA) and composite kernel support vector regression (CK-SVR) to perform the estimation. Firstly, the flotation prior knowledge and KPCA are employed to reduce the dimension of input vector of CK-SVR. Then, considering that the characteristics...
This paper put forward a new method of the SVM and variable structure artificial neural network model for short-term load forecasting. The neural call function is basis of nonlinear wavelets. We overcome the shortcoming of single train set of SVM. It can be seen from the example this method can improve effectively the forecast accuracy and speed. The forecast model was tested and the result showed...
The principle and step of performance evaluation of project management based on SVM and fuzzy rules are studied. The index system of performance evaluation of project management is set up. Then we built up the evaluation model on SVM and fuzzy rules. Finally, take some samples of project for an example, we carry on this model to instance. It can take a preferably evaluation, so that it is a viable...
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