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.
Arterial coordination is a common method in urban traffic control. Traditional arterial coordination methods are usually off-line control methods based on mixed-integer linear program. These methods cannot adapt to changes of traffic flow, for instance, although there are very few cars in a branch road, timing plan will not adjust. Thus, we proposed a semi-actuated arterial coordination method which...
A BP artificial neural network model was established to optimize the final slope angle of open-pit mine, which was based on its powerful self-learning, nonlinear processing capabilities and advantages of simulation for the slope stability with nonlinear relationship among the parameters. The consideration of effect on the stability of the slope includes Protodrakonov scale of hardness, dip angle of...
This paper investigates the problem of output-feedback control for a class of more general stochastic high-order nonlinear systems, which power is a ratio of odd integers. By extending the adding a power integrator technique, introducing a new rescaling transformation, and choosing an appropriate Lyapunov function, an output-feedback controller is constructed to render the closed-loop system globally...
In the analysis of predicting power load forecasting based on least squares neural network, the instability of the time series could lead to decrease of prediction accuracy. On the other hand,neural network and chaos theories parameters must be carefully predetermined in establishing an efficient model. In order to solve the problems mentioned above, in this paper, the neural network and chaos theory...
Transformer faults are quite complicated phenomena and can occur due to a variety of reasons. There have been several methods for transformer fault synthetic diagnosis, but each of them has its own limitations in real fault diagnosis applications. In order to overcome those shortcomings in the existing methods, a new transformer fault diagnosis method based on a wavelet neural network optimized by...
The dynamics of traffic flow influenced by real-time traffic information has become a hot topic. The aim of this paper is to explore the effects of four different information service strategies on travelers' route choice and the resultant system performance in a signal controlled network, where the exact real-time information is more difficult to collect in comparison with the two-route scenario....
Most sensors can not be modeled easily, which leads to the problem that a circuit with sensors can not be simulated in PSPICE. A method based on the neural network for modeling NTC thermistors and creating a NTC thermistor model library for PSPICE is presented to solve the problem. Firstly, a multi-layer feedforward neural network is used to approximate the characteristics of a NTC thermistor. Secondly,...
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.