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.
Residential loan plays an important role for commercial banks to keep away from credit risks. This paper uses neural networks for residential loan, and trains the networks with two evolutional algorithms-genetic algorithm (GA) and particle swarm optimization (PSO). And a GA neural network and a PSO neural network are constructed respectively. The two neural networks are used to classify the residential...
The parameters of support vector machine (SVM) are crucial to the model's classification performance. Aiming at the randomicity of selecting the parameters in SVM, this paper presents a method to optimize the parameters of SVM by using genetic algorithm (GA). Using GA's global search to optimize the parameters of SVM and using the chromosome's fitness function to control the type II error rate in...
With the idea of combining forecasts, this paper presents a new approach by combining multi-linear regression and logistic with RBF network, and applies it in the area of personal credit scoring. The results indicate that the new technique is more accurate than either of the individual technique, especially in avoiding recognizing the bad applicants as good ones.
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.