The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The principle and step of performance evaluation of project management based on SVM and wavelet neural network are studied. The index system of performance evaluation of project management is set up. Then we built up the evaluation model on SVM and wavelet neural network. Finally, take some samples of project for an example, we carry on this model to instance. It can take a preferably evaluation,...
This paper put forward a new method of the SVM and wavelet 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 that it was an effective...
This paper proposes a new method for load forecasting-fuzzy rules by genetic algorithms based on Takagi-Sugeno fuzzy logic system, and establishing the fuzzy model for load forecasting. It can be seen from the example this method can improve effectively the forecast accuracy and speed. It can be applied to the daily electric load forecasting.
This paper proposes a new method for load forecasting-fuzzy rules by genetic algorithms based on Takagi-Sugeno Fuzzy Logic System, and establishing the fuzzy model for load forecasting. It can be seen from the example this method can improve effectively the forecast accuracy and speed. It can be applied to the short-term electric load forecasting.
In the study, neural network theory was used to build a nonlinear model for high precision gyroscope reflecting the relationship between temperature and drift.The result shows that types of neural network and input sample have great influence on model precision. High precision gyroscope is sensitive to temperature. The input sample must take account of the continuous temperature and mean temperature...
In the study, back-propagation neural networks (BP-NN) theory and genetic algorithm (GA) were used to build a nonlinear prediction model reflecting the relationship between technics parameters of electric field aging and mechanical properties of LY12 aluminum alloy. In this model, electric field intensity, aging temperature and time were as input parameters. Tensile strength, yield strength and micro-yield...
Multiple input multiple output (MIMO) radar systems employ the orthogonal signals to improve the system performance. Some results show that there are no complete orthogonal signals in the single code field, even refer to the binary, polyphase and the plural sequences, the maximum of both the auto-correlation function (ACF) and the cross-correlation function (CCF) can not equal to zero at the all delays...
Support vector machine (SVM) plays an important role in the data mining and knowledge discovery by constructing a non-linear optimal classifier. The key problem of training support vector machines is how to solve quadratic programming problem, which results in calculation difficulty while learning samples gets larger. The intelligent search techniques, such as genetic algorithm and particle swarm...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.