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.
This paper deals with a new class of Markov Chain type models that can be effectively used for real time modeling and on-line learning of nonlinear systems with uncertainties. We expand the concept of the generalized Markov Chain - a probabilistic model that synergistically combines the idea of transition probabilities with the information granulation paradigm. We consider generalized Markov chains...
Because of the highly nonlinear of the Traffic flow prediction, it is very difficult to build its model. In this paper an algorithm which is based on fuzzy time series forecasting, is used to overcome the difficulty. And we use Coil-based virtual video detectors detect the traffic flow as a input of fuzzy time series prediction, this can make the historical data collection faster and more accurate...
There is no one standard take for granted in the world, therefore, in this paper, city road-network traffic congestion is divided into road section congestion and cross congestion, and is classified as five classes: congestion, crowd, general crowd, general unimpeded, unimpeded. The indexes for evaluation of city road network traffic congestion are selected, and the two hierarchy evaluation index...
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.