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.
It is deficiency to use accuracy as a measurement to evaluate model classifying ability. This paper proposes a measurement method which uses the area under the ROC curve, or AUC value, to evaluate the performance of the model. Furthermore, applying cross validation and grid-search methods, through designed algorithms, to build an optimization of support vector machines medical prediction model. The...
This paper proposes a new probabilistic method for maximum temperature forecasting in short-term electrical load forecasting. The proposed method makes use of Gaussian process (GP)of the kernel machine to evaluate the predicted temperature. In recent years, electric power markets become more deregulated and competitive. The power system players are concerned with maximizing a profit while minimizing...
A novel model was proposed for short-term electricity price forecasting based on rough set approach and improved support vector machines (SVM). Firstly, we can get reduced information table with no information loss by rough set approach. And then, this reduced information is used to develop classification rules and train SVM, at the same time, we make use of the particle swarm optimization to optimize...
In order to identify the rotating machinery fault, a method based on support vector machine (SVM) is proposed in this paper. After the feature vectors from the fault signals by means of wavelet packet are extracted and the support vector machine (SVM) classification algorithm to the classification of faults in rolling bearing is applied. By drawing a comparison between the classification and BP neural...
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.